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ICCBR
2010
Springer

Imitating Inscrutable Enemies: Learning from Stochastic Policy Observation, Retrieval and Reuse

13 years 7 months ago
Imitating Inscrutable Enemies: Learning from Stochastic Policy Observation, Retrieval and Reuse
In this paper we study the topic of CBR systems learning from observations in which those observations can be represented as stochastic policies. We describe a general framework which encompasses three steps: (1) it observes agents performing actions, elicits stochastic policies representing the agents’ strategies and retains these policies as cases. (2) The agent analyzes the environment and retrieves a suitable stochastic policy. (3) The agent then executes the retrieved stochastic policy, which results in the agent mimicking the previously observed agent. We implement our framework in a system called JuKeCB that observes and mimics players playing games. We present the results of three sets of experiments designed to evaluate our framework. The first experiment demonstrates that JuKeCB performs well when trained against a variety of fixed strategy opponents. The second experiment demonstrates that JuKeCB can also, after training, win against an opponent with a dynamic strategy. Th...
Kellen Gillespie, Justin Karneeb, Stephen Lee-Urba
Added 15 Aug 2010
Updated 15 Aug 2010
Type Conference
Year 2010
Where ICCBR
Authors Kellen Gillespie, Justin Karneeb, Stephen Lee-Urban, Héctor Muñoz-Avila
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