The nature of statistical learning theory
The nature of statistical learning theory
Economic principles of multi-agent systems
Artificial Intelligence - Special issue on economic principles of multi-agent systems
Foundations of statistical natural language processing
Foundations of statistical natural language processing
A social reinforcement learning agent
Proceedings of the fifth international conference on Autonomous agents
Statistical Language Learning
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Population dynamics of grammar acquisition
Simulating the evolution of language
Learning to communicate in a decentralized environment
Autonomous Agents and Multi-Agent Systems
What Are the Unique Design Features of Language? Formal Tools for Comparative Claims
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
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We consider the problem of linguistic agents that communicate with each other about a shared world. We develop a formal notion of a language as a set of probabilistic associations between form (lexical or syntactic) and meaning (semantic) that has general applicability. Using this notion, we define a natural measure of the mutual intelligibility, F(L, L'), between two agents, one using the language L and the other using L'. We then proceed to investigate three important questions within this framework: (1) Given a language L, what language L' maximizes mutual intelligibility with L? We find surprisingly that L' need not be the same as L and we present algorithms for approximating L' arbitrarily well. (2) How can one learn to optimally communicate with a user of language L when L is unknown at the outset and the learner is allowed a finite number of linguistic interactions with the user of L? We describe possible algorithms and calculate explicit bounds on the number of interactions needed. (3) Consider a population of linguistic agents that learn from each other and evolve over time. Will the community converge to a shared language and what is the nature of such a language? We characterize the evolutionarily stable states of a population of linguistic agents in a game-theoretic setting. Our analysis has significance for a number of areas in natural and artificial communication where one studies the design, learning, and evolution of linguistic communication systems.