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Soar

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  • Vim Soar Plug-In

    Vim Soar Plug-In

    This package allows you to edit your Soar files in vim more easily by providing the following capabilities:
    • Syntax highlighting
    • Auto-indenting
    • Moving around by productions
    • Toggling comment/uncomment productions
    • Code folding (You can fold a production into a single line)
    • Taglist support
    Download LinksInstructions

    Download the archive and expand it into $HOME/.vim (C:\Documents and Settings\user\vimfiles in Windows). You should have the following...
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  • Episodic Memory Size Tool

    Episodic Memory Size Tool

    This tool is a command-line python script to determine the size of episodes in episodic memory.

    Download LinksDocumentation
    • None.
    Developer
    • Justin Li
    Soar Versions
    • Any with episodic memory; version must match the one that produced the DB.
    Language
    • Python
    See more | Go to post

  • RoomsWorld

    RoomsWorld

    RoomsWorld is a simulated Soar Robot environment. It is composed of a set of connected rooms, some of which contain blocks. One of the rooms is designated the storage room. The agent's task is to collect the blocks and move them to the storage room. The agent can turn and move forward, and pick up and put down a block. The agent can only carry one block at a time. The agent's movement is continuous and takes time (it turns and moves at a fixed rate). The agent's perception is limited by a vision...
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  • Soar Data Collector

    Soar Data Collector

    A Java library for collecting performance statistics for a running Soar agent.

    Statistics are collected at configurable intervals during a run and include:
    • cumulative cpu usage times
    • number of productions fired
    • working memory size, high and low water marks
    • working memory deltas
    • maximum/minimum decision cycle times, wm deltas, production firings
    • epmem and smem statistics including memory, queries, stores, retrieves
    Download Links...
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  • Soar QnA

    Soar QnA

    SoarQnA facilitates agent access to external knowledge stores via the io system. It is an efficient, unified agent interface that allows your system to access arbitrary external data sources.

    Environment Properties
    • N/A
    Download LinksAssociated Agents
    • QnA Test Agent: An example agent is provided with the download which runs and validates a non-comprehensive set of unit tests based upon available sample data source instances/queries.
    Documentation

    All of these...
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  • State2Dot

    State2Dot

    A command-line python script to convert printed states (e.g. the output of "print -d 100 s1") to a GraphViz DOT file. You can then use that DOT file with GraphViz to produce a graph that can help you visualize the working memory elements that compose the state.

    Download LinksDocumentation
    • None
    Developer
    • Justin Li
    Soar Versions
    • Any
    Language
    • Python
    See more | Go to post

  • Water Jug (Reinforcement Learning)

    Water Jug (Reinforcement Learning)

    This agent demonstrates how to solve the water jug problem using reinforcement learning. It is a modification of the Simple Water Jug Agent. Two main changes are made: templates are used to generate the full space of possible moves that the agent can perform and rewards are set based on the problem solution.

    Soar capabilities
    • Reinforcement learning
    Download LinksExternal Environment
    • None.
    Default Rules
    • None.
    Associated Publications
    • The
    ...
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  • Dice

    Dice

    Dice is a java implementation of a game often called Liar's Dice.

    Here is an abbreviated description of the rules used in our implementation of this domain:
    • Each player gets five six-sided dice and a cup to conceal their dice from other players.
    • To begin each round, all players roll their dice under their cups and look at their new 'hand' while keeping it concealed from the other players. The first player begins bidding, picking a quantity of a face number. The quantity states the
    ...
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  • jSoar

    jSoar

    JSoar is a pure Java implementation of most of Soar.

    While there may be a reduced feature set -- JSoar is based on the 9.0.1 kernel and does not YET include capabilities added after 9.3.4 -- there are a few benefits to a pure-Java implementation of Soar:
    • Idiomatic Java API in contrast to CSoar's SWIG-generated bindings.
    • "Free" multi-language support (JRuby, Jython, Rhino (JavaScript), Groovy, Scala, Clojure, etc)
    • A codebase and tools more friendly to rapid research
    ...
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  • UltraEdit Syntax Coloring Wordfile

    UltraEdit Syntax Coloring Wordfile

    This file allows you to edit Soar files in the cross-platform editor UltraEdit more easily. This file provides the following functionality:
    • Automatic indentation
    • Syntax coloring
    • Mass commenting (select a block of text and un/comment them all in one step)
    • Function lists (a list of all productions in a file will appear in the function list. Click on a function to immediately scroll to it.)
    • Code folding (click on the plus sign next to a production and it will hide all of its contents except
    ...
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  • SoarUnit

    SoarUnit

    SoarUnit is a framework for unit testing Soar code introduced in JSoar 0.10.1. It is implemented as part of JSoar, but it supports running code in either JSoar or CSoar 9.3.1. When run, SoarUnit scans a given directory for test cases (see below) and runs all of the tests that are found. It then reports the test results, either in a text format, or through a user interface similar to the JUnit view in Eclipse.

    Download LinksDocumentation
    • Extensive
    ...
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  • Soar Debugger

    Soar Debugger

    A powerful Soar debugger implemented in Java that interfaces with Soar via SML. The debugger can run a Soar agent within it or hook up remotely to agents running in an environment or another computer.

    Download Links
    • The Soar debugger is included with the SoarSuite release. There is a batch or script file at the top level of the SoarSuite folder that will launch it.
    Documentation
    • An introductory tutorial to the Soar debugger can be found at this page.
    Developers
    • Douglas Pearson
    • Bob
    ...
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  • SoarEditor

    SoarEditor

    The SoarEditor is an Eclipse plugin that allows you to use the powerful Eclipse IDE for writing Soar agents. It provides syntax coloring, auto-indenting, data map construction and generation, attribute/value completion (using the data map) and agent file structure management.

    Download Links

    The SoarEditor is downloadable via Eclipse itself.
    1. Install the latest version of Eclipse.
    2. In Eclipse, go to Help > Install New Software...
    3. Click on the Add... button to add
    ...
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  • Blocks-World (Reinforcement Learning)

    Blocks-World (Reinforcement Learning)

    This agent contains a version of blocks-world that uses reinforcement learning for move-block, which moves a block to a destination.

    Soar capabilities
    • Reinforcement Learning
    Download LinksExternal Environment
    • None.
    Default Rules
    • None.
    Associated PublicationsDeveloper
    • John Laird
    Soar Versions
    • Soar 8,9
    Project Type
    • VisualSoar
    See more | Go to post

  • Blocks-World (Subgoaling with RL)

    Blocks-World (Subgoaling with RL)

    agent incorporates both operator subgoaling/means ends analysis with reinforcement learning. All search control knowledge (operator evaluation rules) are removed from blocks-world-operator-subgoaling and instead there are RL rules supplemented with rules to compute reward, both in the top state and the substate. Implemented for four blocks.

    Soar capabilities
    • Subgoaling with means-ends analysis
    • Reinforcement learning
    Download LinksExternal En...
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  • Water Jug (Look-Ahead with State Evaluation)

    Water Jug (Look-Ahead with State Evaluation)

    This agent is a modification of the Water Jug Simple Agent that demonstrates using a tie impasse to subgoal and evaluate operators. This is an excellent demonstration of look-ahead search and how the selection default rules work.

    Unlike the Water Jug Look-Ahead Agent, the tie agent has knowledge that prefers certain moves over others, for example preferring a pour after a fill operator, so it is able to solve the problem much more efficiently.

    Soar capabilities
    • Look-ahead
    ...
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  • Water Jug (Hierarchical Task Decomposition)

    Water Jug (Hierarchical Task Decomposition)

    This project contains a version of the water jug problem that is formulated for hierarchical task decomposition. It involves two levels of problem spaces. The top level has three operators: fill, empty or pour. The next level consists of three operators: pick-up, fill-jug and put-down and they arise in an operator no-change for the super state.

    Note: This agent works with chunking, which compiles the actions in the substates into rules that apply at the top-state. Use the command "learn...
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  • Water Jug (Look-Ahead)

    Water Jug (Look-Ahead)

    This agent is a modification of the Water Jug Simple Agent that demonstrates using a tie impasse to subgoal and evaluate operators. This is an excellent demonstration of look-ahead search and how the selection default rules work.

    Unlike the Water Jug Look-Ahead Agent with State Evaluation , the look-ahead agent has no knowledge that prefers certain moves over others, so it does exhaustive search which takes far more decision cycles.

    Soar capabilities
    • Look-ahead subgoaling
    • Can
    ...
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  • Taxi (Hierarchical Reinforcement Learning)

    Taxi (Hierarchical Reinforcement Learning)

    This agent simulates an omniscient taxi driver that uses reinforcement learning and hierarchical task decomposition to improve its performance over runs.

    Soar capabilities
    • Hierarchical task decomposition
    • Reinforcement learning
    Download Links
    • The agent is included in the Taxi download.
    External EnvironmentDefault Rules
    • None.
    Associated Publications...
    See more | Go to post

  • Taxi (Reinforcement Learning)

    Taxi (Reinforcement Learning)

    This agent simulates an omniscient taxi driver that uses reinforcement learning to improve its performance over runs.

    Soar capabilities
    • Reinforcement Learning
    Download Links
    • The agent is included in the Taxi download.
    External EnvironmentDefault Rules
    • None.
    Associated PublicationsDevel...
    See more | Go to post
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