diff --git a/RELEASE_NOTES.md b/RELEASE_NOTES.md
index 587ef28df..46deb82f5 100644
--- a/RELEASE_NOTES.md
+++ b/RELEASE_NOTES.md
@@ -2,10 +2,25 @@
 
 ## Current Release
 
+### New Levels:
+
+1.  DMLab-30.
+
+    1.   contributed/dmlab30/psychlab_arbitrary_visuomotor_mapping
+    2.   contributed/dmlab30/psychlab_continuous_recognition
+
+2.  Psychlab.
+
+    1.   contributed/psychlab/arbitrary_visuomotor_mapping
+    2.   contributed/psychlab/continuous_recognition
+
 ### New Features:
 
 1.  Support for level caching for improved performance in the Python module.
 2.  Add the ability to spawn pickups dynamically at arbitrary locations.
+3.  Add implementations to read datasets including Cifar10 and Stimuli.
+4.  Add the ability to specify custom actions via 'customDiscreteActionSpec' and
+    'customDiscreteAction' callbacks.
 
 ### Bug Fixes:
 
diff --git a/game_scripts/factories/psychlab/arbitrary_visuomotor_mapping_factory.lua b/game_scripts/factories/psychlab/arbitrary_visuomotor_mapping_factory.lua
new file mode 100644
index 000000000..34b009a03
--- /dev/null
+++ b/game_scripts/factories/psychlab/arbitrary_visuomotor_mapping_factory.lua
@@ -0,0 +1,454 @@
+--[[ Copyright (C) 2018 Google Inc.
+
+This program is free software; you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation; either version 2 of the License, or
+(at your option) any later version.
+
+This program is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License along
+with this program; if not, write to the Free Software Foundation, Inc.,
+51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+]]
+
+local brady_konkle_oliva2008 = require 'datasets.brady_konkle_oliva2008'
+local game = require 'dmlab.system.game'
+local helpers = require 'common.helpers'
+local psychlab_factory = require 'factories.psychlab.factory'
+local psychlab_helpers = require 'factories.psychlab.helpers'
+local point_and_click = require 'factories.psychlab.point_and_click'
+local random = require 'common.random'
+local tensor = require 'dmlab.system.tensor'
+
+--[[ This task goes by various names in the literature, they include:
+
+---- conditional visuomotor learning
+---- conditional discrimination
+---- arbitrary visuomotor mapping
+
+See Wise & Murray. Trends Neurosci. (2000) 23, 271-276.
+
+It can be seen as a special kind of cued recall task where the item to be
+be recalled is the response itself.  That is, the associations to be learned in
+this task are between images and responses (locations to point at).
+
+This experiment measures how many arbitrary visuomotor maps can be learned and
+maintained in memory for the duration of an episode.
+
+The specific image-response pairs to be remembered are generated anew for each
+episode.
+]]
+
+local TIME_TO_FIXATE_CROSS = 1 -- in frames
+local FAST_INTER_TRIAL_INTERVAL = 1 -- in frames
+local SCREEN_SIZE = {width = 512, height = 512}
+local BG_COLOR = {255, 255, 255}
+local TRIALS_PER_EPISODE_CAP = 60
+
+local TARGET_SIZE = 0.75
+
+local FIXATION_REWARD = 0
+local CORRECT_REWARD = 1
+local INCORRECT_REWARD = 0
+
+local FIXATION_SIZE = 0.1
+local FIXATION_COLOR = {255, 0, 0} -- RGB
+local CENTER = {0.5, 0.5}
+local BUTTON_SIZE = 0.1
+local BUTTONS = {'north', 'south', 'east', 'west'}
+
+local BUTTON_POSITIONS = {
+    north = psychlab_helpers.getUpperLeftFromCenter(
+      {CENTER[1], BUTTON_SIZE / 2}, BUTTON_SIZE),
+    south = psychlab_helpers.getUpperLeftFromCenter(
+      {CENTER[1], 1 - BUTTON_SIZE / 2}, BUTTON_SIZE),
+    east = psychlab_helpers.getUpperLeftFromCenter(
+      {BUTTON_SIZE / 2, CENTER[2]}, BUTTON_SIZE),
+    west = psychlab_helpers.getUpperLeftFromCenter(
+      {1 - BUTTON_SIZE / 2, CENTER[2]}, BUTTON_SIZE)
+}
+
+local factory = {}
+
+function factory.createLevelApi(kwargs)
+  kwargs.timeToFixateCross = kwargs.timeToFixateCross or TIME_TO_FIXATE_CROSS
+  kwargs.fastInterTrialInterval = kwargs.fastInterTrialInterval or
+    FAST_INTER_TRIAL_INTERVAL
+  kwargs.screenSize = kwargs.screenSize or SCREEN_SIZE
+  kwargs.bgColor = kwargs.bgColor or BG_COLOR
+  kwargs.trialsPerEpisodeCap = kwargs.trialsPerEpisodeCap or
+    TRIALS_PER_EPISODE_CAP
+  kwargs.targetSize = kwargs.targetSize or TARGET_SIZE
+  kwargs.fixationReward = kwargs.fixationReward or FIXATION_REWARD
+  kwargs.correctReward = kwargs.correctReward or CORRECT_REWARD
+  kwargs.incorrectReward = kwargs.incorrectReward or INCORRECT_REWARD
+  kwargs.fixationSize = kwargs.fixationSize or FIXATION_SIZE
+  kwargs.fixationColor = kwargs.fixationColor or FIXATION_COLOR
+  kwargs.center = kwargs.center or CENTER
+  kwargs.buttonSize = kwargs.buttonSize or BUTTON_SIZE
+  kwargs.buttons = kwargs.buttons or BUTTONS
+  kwargs.buttonPositions = kwargs.buttonPositions or BUTTON_POSITIONS
+
+  local ARG = {
+      screenSize = kwargs.screenSize,
+      jitter = false,
+  }
+
+  --[[ 'initAssociationsArray' defines the array of associations and its
+  methods.
+  (a 'class')
+  ]]
+  local function initAssociationsArray(dataset)
+    local associations = {
+        _array = {},
+        _order = {},
+        _index = 0
+    }
+
+    local unusedIds = tensor.Int64Tensor{range = {dataset:getSize()}}:shuffle(
+      random:generator())
+    local usedIdCount = 0
+
+    local function getNewId()
+      if usedIdCount < dataset:getSize() then
+        usedIdCount = usedIdCount + 1
+        return unusedIds(usedIdCount):val()
+      else
+        error('Unable to get new image id. Not enough remain.')
+      end
+    end
+
+    function associations:shuffle()
+      local perm = tensor.Int64Tensor{range = {#self._order}}:shuffle(
+        random:generator())
+      for i = 1, #self._order do
+        self._order[i] = perm(i):val()
+      end
+      self._index = 0
+    end
+
+    function associations:add()
+      local association = {
+          imageId = getNewId(),
+          correctResponse = psychlab_helpers.randomFrom(kwargs.buttons),
+          timesPreviouslyDisplayed = 0,
+          mostRecentTrial = -1
+      }
+      table.insert(self._array, association)
+      table.insert(self._order, #self._order + 1)
+    end
+
+    -- 'associations.step' is called during each trial.
+    function associations:step(trialId)
+      self._index = self._index + 1
+
+      -- Copy the association so as to return it before updating its recency
+      -- data.
+      self._output = helpers.shallowCopy(self._array[self._order[
+        self._index]])
+
+      -- Update the recency data.
+      local ref = self._array[self._order[self._index]]
+      ref.timesPreviouslyDisplayed = ref.timesPreviouslyDisplayed + 1
+      ref.mostRecentTrial = trialId
+
+      -- Reset _index if necessary and return.
+      if self._index == #self._array then
+        self._index = 0
+      end
+      return self._output
+    end
+
+    return associations
+  end
+
+  --[[ Function to define the adaptive staircase procedure (a 'class').
+  This procedure promotes from difficulty level K to level K + 1 when K
+  consecutive trials are correct.
+  ]]
+  local function initStaircase(opt)
+    local staircase = {
+        _difficultyLevel = 1,
+        _perfectSoFar = true,
+        _index = 0,
+        _promoteLevel = opt.promoteFunction,
+        _repeatLevel = opt.repeatFunction
+    }
+
+    function staircase.promoteLevel(self)
+      self._difficultyLevel = self._difficultyLevel + 1
+      self._promoteLevel()
+    end
+
+    function staircase.repeatLevel(self)
+      self._repeatLevel()
+    end
+
+    function staircase.endLevel(self)
+      if self._perfectSoFar then
+        self:promoteLevel()
+      else
+        self:repeatLevel()
+      end
+      self._perfectSoFar = true
+    end
+
+    -- 'staircase.step' is called at the end of each trial.
+    function staircase.step(self, correct)
+      self._index = self._index + 1
+
+      -- Track whether all trials are correct.
+      if correct ~= 1 then
+        self._perfectSoFar = false
+      end
+
+      -- Reset _index if necessary and call the endLevel function.
+      if self._index == self._difficultyLevel then
+        self._index = 0
+        self:endLevel()
+      end
+    end
+
+    return staircase
+  end
+
+  -- Class definition for arbitrary visuomotor mapping psychlab environment.
+  local env = {}
+  env.__index = env
+
+  setmetatable(env, {
+      __call = function (cls, ...)
+        local self = setmetatable({}, cls)
+        self:_init(...)
+        return self
+      end
+  })
+
+  -- 'init' gets called at the start of each episode.
+  function env:_init(pac, opts)
+    print('opts passed to _init:')
+    print(helpers.tostring(opts))
+    print('ARG in _init:')
+    print(helpers.tostring(ARG))
+
+    if self.dataset == nil then
+      self.dataset = brady_konkle_oliva2008(opts)
+    end
+
+    self.screenSize = opts.screenSize
+
+    -- If requested, randomly perturb the target location for each trial.
+    self.jitter = ARG.jitter
+    if self.jitter then
+      print('Jitter target location')
+      self.jitteredCenter = {}
+    end
+
+    self:setupImages()
+
+    -- Store a copy of the 'point_and_click' api.
+    self.pac = pac
+  end
+
+  --[[ Reset is called after init. It is called only once per episode.
+  Note: the episodeId passed to this function may not be correct if the job
+  has resumed from a checkpoint after preemption.
+  ]]
+  function env:reset(episodeId, seed)
+    random:seed(seed)
+
+    self.pac:setBackgroundColor(kwargs.bgColor)
+    self.pac:clearWidgets()
+    psychlab_helpers.addFixation(self, kwargs.fixationSize)
+
+    self.currentTrial = {}
+    self._previousTrialId = 0
+
+    psychlab_helpers.setTrialsPerEpisodeCap(self, kwargs.trialsPerEpisodeCap)
+
+    -- Initialize associations array and adaptive staircase objects.
+    self.associations = initAssociationsArray(self.dataset)
+    self.staircase = initStaircase{
+        repeatFunction = function ()
+          self.associations:shuffle()
+        end,
+        promoteFunction = function ()
+          self.associations:add()
+          self.associations:shuffle()
+        end
+    }
+
+    -- Start out with one association in the array. Do this after the seed has
+    -- been set.
+    self.associations:add()
+  end
+
+  function env:setupImages()
+    self.images = {}
+
+    self.images.fixation = psychlab_helpers.getFixationImage(self.screenSize,
+      kwargs.bgColor, kwargs.fixationColor, kwargs.fixationSize)
+
+    local h = kwargs.buttonSize * self.screenSize.height
+    local w = kwargs.buttonSize * self.screenSize.width
+
+    self.images.greenImage = tensor.ByteTensor(h, w, 3)
+    self.images.greenImage:select(3, 1):fill(100)
+    self.images.greenImage:select(3, 2):fill(255)
+    self.images.greenImage:select(3, 3):fill(100)
+
+    self.images.dullGreenImage = tensor.ByteTensor(h, w, 3)
+    self.images.dullGreenImage:select(3, 1):fill(100)
+    self.images.dullGreenImage:select(3, 2):fill(200)
+    self.images.dullGreenImage:select(3, 3):fill(100)
+
+    self.images.redImage = tensor.ByteTensor(h, w, 3)
+    self.images.redImage:select(3, 1):fill(255)
+    self.images.redImage:select(3, 2):fill(100)
+    self.images.redImage:select(3, 3):fill(100)
+
+    self.images.dullRedImage = tensor.ByteTensor(h, w, 3)
+    self.images.dullRedImage:select(3, 1):fill(200)
+    self.images.dullRedImage:select(3, 2):fill(100)
+    self.images.dullRedImage:select(3, 3):fill(100)
+
+    self.images.whiteImage = tensor.ByteTensor(h, w, 3):fill(255)
+    self.images.blackImage = tensor.ByteTensor(h, w, 3)
+
+    self.target = tensor.ByteTensor(256, 256, 3)
+  end
+
+  function env:finishTrial(delay)
+    self.currentTrial.memorySetSize = #self.associations._array
+    self.currentTrial.reactionTime =
+      game:episodeTimeSeconds() - self._currentTrialStartTime
+    -- It is necessary to record memorySetSize before stepping the staircase.
+    self.staircase:step(self.currentTrial.correct)
+
+    self.currentTrial.stepCount = self.pac:elapsedSteps()
+    psychlab_helpers.publishTrialData(self.currentTrial, kwargs.schema)
+    psychlab_helpers.finishTrialCommon(self, delay, kwargs.fixationSize)
+  end
+
+  function env:fixationCallback(name, mousePos, hoverTime, userData)
+    if hoverTime == kwargs.timeToFixateCross then
+      self.pac:addReward(kwargs.fixationReward)
+      self.pac:removeWidget('fixation')
+      self.pac:removeWidget('center_of_fixation')
+
+      self.currentTrial.trialId = self._previousTrialId + 1
+      -- Measure reaction time since the trial started.
+      self._currentTrialStartTime = game:episodeTimeSeconds()
+      self.pac:resetSteps()
+
+      -- 'trialId' must be set before adding array to compute recency.
+      self:addArray(self.currentTrial.trialId)
+    end
+  end
+
+  function env:revealCorrectResponse()
+    for _, button in ipairs(kwargs.buttons) do
+      if button == self.currentTrial.correctResponse then
+        self.pac:updateWidget(button, self.images.greenImage)
+      else
+        self.pac:updateWidget(button, self.images.redImage)
+      end
+    end
+  end
+
+  function env:onHoverEnd(name, mousePos, hoverTime, userData)
+    self.pac:addReward(self._rewardToDeliver)
+    self:finishTrial(kwargs.fastInterTrialInterval)
+  end
+
+  function env:correctResponseCallback(name, mousePos, hoverTime, userData)
+    self.currentTrial.response = name
+    self.currentTrial.correct = 1
+    self._rewardToDeliver = kwargs.correctReward
+
+    self:revealCorrectResponse()
+  end
+
+  function env:incorrectResponseCallback(name, mousePos, hoverTime, userData)
+    self.currentTrial.response = name
+    self.currentTrial.correct = 0
+    self._rewardToDeliver = kwargs.incorrectReward
+
+    self:revealCorrectResponse()
+  end
+
+  function env:addResponseButtons()
+    for _, button in ipairs(kwargs.buttons) do
+      local callback
+      if button == self.currentTrial.correctResponse then
+        callback = self.correctResponseCallback
+      else
+        callback = self.incorrectResponseCallback
+      end
+
+      -- When an association is shown for the first time, show the correct
+      -- answer.
+      local buttonImage
+      if self.currentTrial.timesPreviouslyDisplayed > 0 then
+        buttonImage = self.images.blackImage
+      else
+        if button == self.currentTrial.correctResponse then
+          buttonImage = self.images.dullGreenImage
+        else
+          buttonImage = self.images.dullRedImage
+        end
+      end
+
+      self.pac:addWidget{
+          name = button,
+          image = buttonImage,
+          pos = kwargs.buttonPositions[button],
+          size = {kwargs.buttonSize, kwargs.buttonSize},
+          mouseHoverCallback = callback,
+          mouseHoverEndCallback = self.onHoverEnd,
+      }
+    end
+  end
+
+  function env:getNextTrial(trialId)
+    local pair = self.associations:step(trialId)
+    self.currentTrial.imageIndex = pair.imageId
+    self.currentTrial.correctResponse = pair.correctResponse
+
+    self.currentTrial.timesPreviouslyDisplayed = pair.timesPreviouslyDisplayed
+
+    if pair.mostRecentTrial > 0 then
+      self.currentTrial.recency = trialId - pair.mostRecentTrial
+    else
+      -- 'recency' is -1 the first time a new association is introduced.
+      self.currentTrial.recency = -1
+    end
+  end
+
+  function env:addArray(trialId)
+    self:getNextTrial(trialId)
+    psychlab_helpers.addTargetImage(self,
+                                    self.dataset:getImage(
+                                      self.currentTrial.imageIndex),
+                                    kwargs.targetSize)
+    self:addResponseButtons()
+  end
+
+  function env:removeArray()
+    self.pac:removeWidget('target')
+    for _, button in ipairs(kwargs.buttons) do
+      self.pac:removeWidget(button)
+    end
+  end
+
+  return psychlab_factory.createLevelApi{
+      env = point_and_click,
+      envOpts = {environment = env, screenSize = ARG.screenSize}
+  }
+end
+
+return factory
diff --git a/game_scripts/factories/psychlab/continuous_recognition_factory.lua b/game_scripts/factories/psychlab/continuous_recognition_factory.lua
new file mode 100644
index 000000000..c0fc5f7a5
--- /dev/null
+++ b/game_scripts/factories/psychlab/continuous_recognition_factory.lua
@@ -0,0 +1,315 @@
+--[[ Copyright (C) 2018 Google Inc.
+
+This program is free software; you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation; either version 2 of the License, or
+(at your option) any later version.
+
+This program is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License along
+with this program; if not, write to the Free Software Foundation, Inc.,
+51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+]]
+
+local brady_konkle_oliva2008 = require 'datasets.brady_konkle_oliva2008'
+local game = require 'dmlab.system.game'
+local helpers = require 'common.helpers'
+local psychlab_factory = require 'factories.psychlab.factory'
+local psychlab_helpers = require 'factories.psychlab.helpers'
+local point_and_click = require 'factories.psychlab.point_and_click'
+local random = require 'common.random'
+local tensor = require 'dmlab.system.tensor'
+
+--[[ In each trial, the agent must indicate whether an image is old or new.
+50% of the time the answer is new. The set of old images keeps growing.
+
+Unlike most probe recognition paradigms, in this continuous recognition paradigm
+there are no separate study and test phases.
+
+It is a 'varied mapping' paradigm since the same images can appear in different
+orders in different episodes. This terminology is standard. It comes from
+Schneider & Shifrin (1977).
+]]
+
+local TIME_TO_FIXATE_CROSS = 1 -- in frames
+local FAST_INTER_TRIAL_INTERVAL = 1 -- in frames
+local BG_COLOR = {255, 255, 255}
+local TRIALS_PER_EPISODE_CAP = 60
+
+local TARGET_SIZE = 0.75
+
+local FIXATION_REWARD = 0
+local CORRECT_REWARD = 1
+local INCORRECT_REWARD = 0
+local FIXATION_SIZE = 0.1
+local FIXATION_COLOR = {255, 0, 0} -- RGB
+local BUTTON_WIDTH = 0.1
+local BUTTON_HEIGHT = 0.1
+
+local factory = {}
+
+function factory.createLevelApi(kwargs)
+  kwargs.timeToFixateCross = kwargs.timeToFixateCross or TIME_TO_FIXATE_CROSS
+  kwargs.fastInterTrialInterval = kwargs.fastInterTrialInterval or
+    FAST_INTER_TRIAL_INTERVAL
+  kwargs.bgColor = kwargs.bgColor or BG_COLOR
+  kwargs.trialsPerEpisodeCap = kwargs.trialsPerEpisodeCap or
+    TRIALS_PER_EPISODE_CAP
+  kwargs.targetSize = kwargs.targetSize or TARGET_SIZE
+  kwargs.fixationReward = kwargs.fixationReward or FIXATION_REWARD
+  kwargs.correctReward = kwargs.correctReward or CORRECT_REWARD
+  kwargs.incorrectReward = kwargs.incorrectReward or INCORRECT_REWARD
+  kwargs.fixationSize = kwargs.fixationSize or FIXATION_SIZE
+  kwargs.fixationColor = kwargs.fixationColor or FIXATION_COLOR
+  kwargs.buttonWidth = kwargs.buttonWidth or BUTTON_WIDTH
+  kwargs.buttonHeight = kwargs.buttonHeight or BUTTON_HEIGHT
+
+  local ARG = {
+      screenSize = {width = 512, height = 512},
+      jitter = false,
+  }
+
+  -- Class definition for continuous recognition psychlab environment.
+  local env = {}
+  env.__index = env
+
+  setmetatable(env, {
+      __call = function (cls, ...)
+        local self = setmetatable({}, cls)
+        self:_init(...)
+        return self
+      end
+  })
+
+  -- 'init' gets called at the start of each episode.
+  function env:_init(pac, opts)
+    print('opts passed to _init:')
+    print(helpers.tostring(opts))
+    print('ARG in _init:')
+    print(helpers.tostring(ARG))
+
+    if self.dataset == nil then
+      self.dataset = brady_konkle_oliva2008(opts)
+    end
+
+    self.screenSize = opts.screenSize
+
+    -- If requested, randomly perturb the target location for each trial.
+    self.jitter = ARG.jitter
+    if self.jitter then
+      print('Jitter target location')
+      self.jitteredCenter = {}
+    end
+
+    self:setupImages()
+
+    -- Store a copy of the 'point_and_click' api.
+    self.pac = pac
+  end
+
+  -- 'env:setupOrder' determines the order in which images are shown.
+  function env:setupOrder()
+    local firstTrial = true
+    local newIDs = tensor.Int64Tensor{range = {self.dataset:getSize()}}:shuffle(
+      random:generator())
+    self._oldIDs = {}
+    self._trialLastDisplayed = {}
+    self._timesPreviouslyDisplayed = {}
+
+    local function newTrial(trialId)
+      assert(#self._oldIDs < self.dataset:getSize(),
+             'Unable to get new trial id.')
+      local stimID = newIDs(#self._oldIDs + 1):val()
+      table.insert(self._oldIDs, stimID)
+      table.insert(self._trialLastDisplayed, trialId)
+      table.insert(self._timesPreviouslyDisplayed, 0)
+
+      self.currentTrial.imageIndex = stimID
+      self.currentTrial.isNew = true
+      -- 'recency' is -1 the first time a new association is introduced.
+      self.currentTrial.recency = -1
+      self.currentTrial._timesPreviouslyDisplayed = 0
+
+      return self.currentTrial.imageIndex, self.currentTrial.isNew
+    end
+
+    local function oldTrial(trialId)
+      local stimID, stimIndex = psychlab_helpers.randomFrom(self._oldIDs)
+
+      self.currentTrial.imageIndex = stimID
+      self.currentTrial.isNew = false
+      -- 'recency' denotes the number of trials since item was last shown.
+      self.currentTrial.recency = trialId - self._trialLastDisplayed[stimIndex]
+      self.currentTrial._timesPreviouslyDisplayed =
+        self._timesPreviouslyDisplayed[stimIndex]
+
+      -- Keep track of the last trial id when each oldID was last shown.
+      self._trialLastDisplayed[stimIndex] = trialId
+      self._timesPreviouslyDisplayed[stimIndex] =
+        self._timesPreviouslyDisplayed[stimIndex] + 1
+      return self.currentTrial.imageIndex, self.currentTrial.isNew
+    end
+
+    self.getNextTrial = function (trialId)
+      if firstTrial then
+        firstTrial = false
+        return newTrial(trialId)
+      else
+        if #self._oldIDs < self.dataset:getSize() and
+           random:uniformReal(0, 1) > .5 then
+          return newTrial(trialId)
+        else
+          return oldTrial(trialId)
+        end
+      end
+    end
+  end
+
+  --[[ Reset is called after init. It is called only once per episode.
+  Note: the episodeId passed to this function may not be correct if the job
+  has resumed from a checkpoint after preemption.
+  ]]
+  function env:reset(episodeId, seed, ...)
+    random:seed(seed)
+
+    self.pac:setBackgroundColor(kwargs.bgColor)
+    self.pac:clearWidgets()
+    psychlab_helpers.addFixation(self, kwargs.fixationSize)
+
+    self.currentTrial = {}
+    self._previousTrialId = 0
+
+    psychlab_helpers.setTrialsPerEpisodeCap(self, kwargs.trialsPerEpisodeCap)
+
+    self:setupOrder()
+  end
+
+  function env:setupImages()
+    self.images = {}
+
+    self.images.fixation = psychlab_helpers.getFixationImage(self.screenSize,
+                                                    kwargs.bgColor,
+                                                    kwargs.fixationColor,
+                                                    kwargs.fixationSize)
+
+    local h = kwargs.buttonHeight * self.screenSize.height
+    local w = kwargs.buttonWidth * self.screenSize.width
+
+    self.images.greenImage = tensor.ByteTensor(h, w, 3)
+    self.images.greenImage:select(3, 1):fill(100)
+    self.images.greenImage:select(3, 2):fill(255)
+    self.images.greenImage:select(3, 3):fill(100)
+
+    self.images.redImage = tensor.ByteTensor(h, w, 3)
+    self.images.redImage:select(3, 1):fill(255)
+    self.images.redImage:select(3, 2):fill(100)
+    self.images.redImage:select(3, 3):fill(100)
+
+    self.images.whiteImage = tensor.ByteTensor(h, w, 3):fill(255)
+    self.images.blackImage = tensor.ByteTensor(h, w, 3)
+
+    self.target = tensor.ByteTensor(256, 256, 3)
+  end
+
+  function env:finishTrial(delay)
+    self.currentTrial.memorySetSize = #self._oldIDs
+    self.currentTrial.reactionTime =
+      game:episodeTimeSeconds() - self._currentTrialStartTime
+    self.currentTrial.stepCount = self.pac:elapsedSteps()
+    psychlab_helpers.publishTrialData(self.currentTrial, kwargs.schema)
+    psychlab_helpers.finishTrialCommon(self, delay, kwargs.fixationSize)
+  end
+
+  function env:fixationCallback(name, mousePos, hoverTime, userData)
+    if hoverTime == kwargs.timeToFixateCross then
+      self.pac:addReward(kwargs.fixationReward)
+      self.pac:removeWidget('fixation')
+      self.pac:removeWidget('center_of_fixation')
+
+      self.currentTrial.trialId = self._previousTrialId + 1
+      -- Measure reaction time since the trial started.
+      self._currentTrialStartTime = game:episodeTimeSeconds()
+      self.pac:resetSteps()
+
+      -- 'trialId' must be set before adding array to compute recency.
+      self:addArray(self.currentTrial.trialId)
+    end
+  end
+
+  function env:onHoverEnd(name, mousePos, hoverTime, userData)
+    self.pac:addReward(self._rewardToDeliver)
+    self:finishTrial(kwargs.fastInterTrialInterval)
+  end
+
+  function env:correctResponseCallback(name, mousePos, hoverTime, userData)
+    self.currentTrial.response = name
+    self.currentTrial.correct = 1
+
+    self.pac:updateWidget(name, self.images.greenImage)
+    self._rewardToDeliver = kwargs.correctReward
+  end
+
+  function env:incorrectResponseCallback(name, mousePos, hoverTime, userData)
+    self.currentTrial.response = name
+    self.currentTrial.correct = 0
+
+    self.pac:updateWidget(name, self.images.redImage)
+    self._rewardToDeliver = kwargs.incorrectReward
+  end
+
+  function env:addResponseButtons(isNew)
+    local buttonPosY = 0.5 - kwargs.buttonHeight / 2
+    local buttonSize = {kwargs.buttonWidth, kwargs.buttonHeight}
+
+    local newCallback, oldCallback
+    if isNew then
+      newCallback = self.correctResponseCallback
+      oldCallback = self.incorrectResponseCallback
+    else
+      newCallback = self.incorrectResponseCallback
+      oldCallback = self.correctResponseCallback
+    end
+
+    self.pac:addWidget{
+        name = 'newButton',
+        image = self.images.blackImage,
+        pos = {0, buttonPosY},
+        size = buttonSize,
+        mouseHoverCallback = newCallback,
+        mouseHoverEndCallback = self.onHoverEnd,
+    }
+    self.pac:addWidget{
+        name = 'oldButton',
+        image = self.images.blackImage,
+        pos = {1 - kwargs.buttonWidth, buttonPosY},
+        size = buttonSize,
+        mouseHoverCallback = oldCallback,
+        mouseHoverEndCallback = self.onHoverEnd,
+    }
+  end
+
+  function env:addArray(trialId)
+    self.currentTrial.imageIndex, self.currentTrial.isNew =
+      self.getNextTrial(trialId)
+    local img = self.dataset:getImage(self.currentTrial.imageIndex)
+    psychlab_helpers.addTargetImage(self, img, kwargs.targetSize)
+    self:addResponseButtons(self.currentTrial.isNew)
+  end
+
+  function env:removeArray()
+    self.pac:removeWidget('target')
+    self.pac:removeWidget('newButton')
+    self.pac:removeWidget('oldButton')
+  end
+
+  return psychlab_factory.createLevelApi{
+      env = point_and_click,
+      envOpts = {environment = env, screenSize = ARG.screenSize}
+  }
+end
+
+return factory
diff --git a/game_scripts/levels/contributed/dmlab30/README.md b/game_scripts/levels/contributed/dmlab30/README.md
index a5eb8772f..8afa2825b 100644
--- a/game_scripts/levels/contributed/dmlab30/README.md
+++ b/game_scripts/levels/contributed/dmlab30/README.md
@@ -2,8 +2,7 @@
 
 DMLab-30 is a set of environments designed for DeepMind Lab. These environments
 enable a researcher to develop agents for a large spectrum of interesting tasks
-either individually or in a multi-task setting. We have released 28 levels. Two
-remaining levels will be added soon.
+either individually or in a multi-task setting.
 
 1.  [`rooms_collect_good_objects_{test,train}`](#collect-good-objects)
 1.  [`rooms_exploit_deferred_effects_{test,train}`](#exploit-deferred-effects)
@@ -23,6 +22,8 @@ remaining levels will be added soon.
 1.  [`natlab_varying_map_randomized`](#varying-map-randomized)
 1.  [`skymaze_irreversible_path_hard`](#irreversible-path-hard)
 1.  [`skymaze_irreversible_path_varied`](#irreversible-path-varied)
+1.  [`psychlab_arbitrary_visuomotor_mapping`](#arbitrary-visuomotor-mapping)
+1.  [`psychlab_continuous_recognition`](#continuous-recognition)
 1.  [`psychlab_sequential_comparison`](#sequential-comparison)
 1.  [`psychlab_visual_search`](#visual-search)
 1.  [`explore_object_locations_small`](#object-locations-small)
@@ -569,6 +570,34 @@ Level Name: `skymaze_irreversible_path_varied`
 For details, see:
 [Leibo, Joel Z. et al. "Psychlab: A Psychology Laboratory for Deep Reinforcement Learning Agents (2018)"](https://arxiv.org/abs/1801.08116).
 
+### Arbitrary Visuomotor Mapping
+
+In this task, the agent is shown consecutive images with which they must
+remember associations with specific movement patterns (locations to point at).
+The agent is rewarded if it can remember the action associated with a given
+object. The images are drawn from a set of ~ 2500, and the specific associations
+are randomly generated and different in each episode.
+
+Test Regime: Training and testing levels drawn from the same distribution.
+
+Observation Spec: RGBD
+
+Level Name: `psychlab_arbitrary_visuomotor_mapping`
+
+### Continuous Recognition
+
+This task tests familiarity memory. Consecutive images are shown, and the agent
+must indicate whether or not they have seen the image before during that
+episode. Looking at the left square indicates no, and right indicates yes. The
+images (drawn from a set of ~2500) are shown in a different random order in
+every episode.
+
+Test Regime: Training and testing levels drawn from the same distribution.
+
+Observation Spec: RGBD
+
+Level Name: `psychlab_continuous_recognition`
+
 ### Sequential Comparison
 
 <div align="center">
diff --git a/game_scripts/levels/contributed/dmlab30/psychlab_arbitrary_visuomotor_mapping.lua b/game_scripts/levels/contributed/dmlab30/psychlab_arbitrary_visuomotor_mapping.lua
new file mode 100644
index 000000000..06159558b
--- /dev/null
+++ b/game_scripts/levels/contributed/dmlab30/psychlab_arbitrary_visuomotor_mapping.lua
@@ -0,0 +1,20 @@
+--[[ Copyright (C) 2018 Google Inc.
+
+This program is free software; you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation; either version 2 of the License, or
+(at your option) any later version.
+
+This program is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License along
+with this program; if not, write to the Free Software Foundation, Inc.,
+51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+]]
+
+local factory = require 'factories.psychlab.arbitrary_visuomotor_mapping_factory'
+
+return factory.createLevelApi{}
diff --git a/game_scripts/levels/contributed/dmlab30/psychlab_continuous_recognition.lua b/game_scripts/levels/contributed/dmlab30/psychlab_continuous_recognition.lua
new file mode 100644
index 000000000..84ab9f10d
--- /dev/null
+++ b/game_scripts/levels/contributed/dmlab30/psychlab_continuous_recognition.lua
@@ -0,0 +1,20 @@
+--[[ Copyright (C) 2018 Google Inc.
+
+This program is free software; you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation; either version 2 of the License, or
+(at your option) any later version.
+
+This program is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License along
+with this program; if not, write to the Free Software Foundation, Inc.,
+51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+]]
+
+local factory = require 'factories.psychlab.continuous_recognition_factory'
+
+return factory.createLevelApi{}
diff --git a/game_scripts/levels/contributed/psychlab/arbitrary_visuomotor_mapping.lua b/game_scripts/levels/contributed/psychlab/arbitrary_visuomotor_mapping.lua
new file mode 100644
index 000000000..2e2288a5d
--- /dev/null
+++ b/game_scripts/levels/contributed/psychlab/arbitrary_visuomotor_mapping.lua
@@ -0,0 +1,23 @@
+--[[ Copyright (C) 2018 Google Inc.
+
+This program is free software; you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation; either version 2 of the License, or
+(at your option) any later version.
+
+This program is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License along
+with this program; if not, write to the Free Software Foundation, Inc.,
+51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+]]
+
+local factory = require 'factories.psychlab.arbitrary_visuomotor_mapping_factory'
+
+return factory.createLevelApi{
+    schema = 'arbitrary_visuomotor_mapping',
+    episodeLengthSeconds = 300,
+}
diff --git a/game_scripts/levels/contributed/psychlab/continuous_recognition.lua b/game_scripts/levels/contributed/psychlab/continuous_recognition.lua
new file mode 100644
index 000000000..84403de10
--- /dev/null
+++ b/game_scripts/levels/contributed/psychlab/continuous_recognition.lua
@@ -0,0 +1,23 @@
+--[[ Copyright (C) 2018 Google Inc.
+
+This program is free software; you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation; either version 2 of the License, or
+(at your option) any later version.
+
+This program is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License along
+with this program; if not, write to the Free Software Foundation, Inc.,
+51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+]]
+
+local factory = require 'factories.psychlab.continuous_recognition_factory'
+
+return factory.createLevelApi{
+    schema = 'continuous_recognition',
+    episodeLengthSeconds = 300,
+}