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Agents

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In this category, you'll find a variety of agents developed for a wide range of different tasks and environments. You will find a full description of the agent, its capabilities and problem solving approach as well, as a download link. If the agent requires an environment, a link will be provided. We'd highly encourage you to submit your own agents for use by the greater Soar community. To do so, you can send your zipped up submission with a full description (try to include all of the type of information we include on each download page) to mazina@umich.edu with the subject "Soar Agent Submission".

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  • Water Jug (Simple)

    Water Jug (Simple)

    These Soar productions implement the water-jug task. The task is to find the sequence of steps that fill the three gallon jug with one gallon of water. There are a well that has an infinite amount of water, a five gallon jug, and a three gallon jug.

    The task problem space has three operators: empty, fill, and pour. Empty empties a jug into the well. Fill fills up a jug from the well. Pour pours some or all of the contents from one jug into the other jug. Pour can only pour out the contents...
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  • Tower of Hanoi (Simple)

    Tower of Hanoi (Simple)

    This agent solves the Tower of Hanoi problems. This puzzle "involves three vertical pegs or posts and a number of doughnut-like disks of graduated sizes that fit on the pegs. At the outset, all the disks are arranged pyramidally on one of the pegs, say A, with the largest disk on the bottom. The task is to move all of the disks to another peg, C, say, under the constraints that (1) only one disk may be moved at a time, and (2) a disk may never be placed on top of another smaller than itself....
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  • Tower of Hanoi (Recursive)

    Tower of Hanoi (Recursive)

    This agent solves the problem using a recursive strategy. It tries to always moves the biggest out of place disk into its correct position. The general description of the task from the Simple Tower of Hanoi Agent still applies.

    Soar capabilities
    • Basic PSCM functions: State Elaboration, Operator Proposal, Operator Evaluation, Internal Operator Application
    • Recursive problem solving
    Download LinksExternal Environment
    • None.
    Default Rules
    • None.
    Associated...
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  • 15-puzzle

    15-puzzle

    This agent is a straightforward implementation of the fifteen-puzzle. It uses look-ahead search to solve the puzzle with a simple evaluation function. This agent also demonstrates chunking.

    The puzzle consists of fifteen sliding tiles, numbered by digits from 1 to 15 arranged in a 4 by 4 array of sixteen cells. One of the cells is always empty, and any adjacent tile can be moved into the empty cell. The initial state is some arbitrary arrangement of the tiles. The goal state is the...
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  • 8-Puzzle

    8-Puzzle

    This agent is a straightforward implementation of an eight-puzzle. It uses look-ahead search to solve the puzzle with a simple evaluation function. This agent also demonstrates chunking.

    The puzzle consists of eight sliding tiles, numbered by digits from 1 to 8 arranged in a 3 by 3 array of nine cells. One of the cells is always empty, and any adjacent tile can be moved into the empty cell. The initial state is some arbitrary arrangement of the tiles. The goal state is the arrangement...
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  • TankSoar (Obscure Bot)

    TankSoar (Obscure Bot)

    The Obscure-bot is an advanced bot that uses mapping. This is a good bot to test your own bot against. To avoid competitors using its code or reverse engineering it, the productions have been saved in a binary form and many of the original names have been replaced by obscure symbols.

    To use the Obscure-bot, load in the file obscure-bot through the tank-soar control panel. This in turn loads in the binary file obscure-bot.soarx.

    Alternatively, you can create a tank using...
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  • TankSoar (Mapping)

    TankSoar (Mapping)

    This agent extends the capabilities of both the TankSoar simple agent (described here) and the TankSoar simple sound agent (described here) with the ability to create an internal representation of the environment map. It uses this map to better control its radar and find chargers.

    Soar capabilities
    • Hierarchical task composition
    • Creating persistent working memory structures to remember past state
    Download Links
    • This agent is packaged with the TankSoar environment.
    External Envir...
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  • TankSoar (Simple Sound)

    TankSoar (Simple Sound)

    This agent extends the capabilities of the TankSoar simple agent (described here) with the ability to remember hearing where another tank is. The agent can then continue to try to chase the other tank even if it can no longer sense it.

    Soar capabilities
    • Hierarchical task composition
    • Creating persistent working memory structures to remember past state
    Download Links
    • This agent is packaged with the TankSoar environment.
    External EnvironmentDefault Rules
    • None.
    Associated...
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  • TankSoar (Wander)

    TankSoar (Wander)

    This is a very simple agent that wanders the map and adjusts its radar power.

    Wandering consists of moving around the map, using sensors to avoid bumping into obstacles and to detect other objects. To best utilize a tank's radar, which works from the front of the tank this agent prefers to move forward and turn only to avoid obstacles. The radar uses up energy, so it attempts to use it sparingly. The simplest thing to do is to turn on the radar when the tank turns, and turn it off if...
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  • TankSoar (Simple)

    TankSoar (Simple)

    This agent implements a tank that wanders around the board looking for objects. It is also able to chase and attack other agents, as well as retreat.

    The agent uses abstract operators that it decomposes into complex combinations of low-level actions. The tank uses its knowledge to select between these activities based on the current situation, just as it selects between different operators. Both of these problems are handled in Soar by allowing abstract high-level operators to be implemented...
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