A stochastic language for modelling opponent agents

There are numerous cases where a reasoning agent needs to reason about the behavior of an opponent agent. In this paper, we propose a hybrid probabilistic logic language within which we can express what actions an opponent may take in a given situation. We present the syntaxis and semantics of the language, and the concept of a Maximally Probable Course of Action. Categories and Subject Descriptors I.2 [Computing Methodolgies]: Artificial Intelligence Keywords Logic for agent systems, Formal models of agency

• Type: Conference
• Year: 2006
• Where: ATAL
• Authors: Gerardo I. Simari, Amy Sliva, Dana S. Nau, V. S. Subrahmanian
• Keywords: ATAL 2006, Hybrid Probabilistic Logic, Intelligent Agents, Opponent Agent, Reasoning Agent