The taxicab problem domain is well known in the area of reinforcement learning. Simply put, a taxicab driver is tasked with the problem of picking up a passenger and delivering him to his destination in as few steps as possible. Typically, the taxi is constrained by a limit on the amount of fuel that can be carried.
The canonical taxicab problem is a 5x5 gridworld. There are four cells which serve as possible starting locations and possible destinations for the passenger. There is a...
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Infinite Mario RL
- Created by: Soar
- Published: 10-08-2014, 12:49 PM
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in DomainsInfinite Mario RL
This environment is derived from the Infinite Mario domain from RLCompetition2009 (based on RL-Glue) and uses SML to connect to Soar.
Agents play a variant of Super Mario, a complete side-scrolling video game with destructible blocks, enemies, fireballs, coins, chasms, platforms, etc. The state space is complicated, but factored in an object-oriented way, which captures many aspects of the real world. Challenges include:- Path planning: How can Mario navigate around simple obstacles,
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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