Learning regular sets from queries and counterexamples
Information and Computation
Online learning about other agents in a dynamic multiagent system
AGENTS '98 Proceedings of the second international conference on Autonomous agents
Introduction To Automata Theory, Languages, And Computation
Introduction To Automata Theory, Languages, And Computation
DFA Learning of Opponent Strategies
Proceedings of the Eleventh International Florida Artificial Intelligence Research Society Conference
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This paper demonstrates the use of recursive modelling of opponent agents in an adversarial environment. In many adversarial environments, agents need to model their opponents and other environmental objects to predict their actions in order to outperform them. In this work, we use Deterministic Finite Automata (DFA) for modelling agents. We also assume that all the actions performed by agents are regular. Every agent assumes that other agents use the same model as its own but without recursion. The objective of this work is to investigate if recursive modelling allows an agent to outperform its opponents that are using similar models.