Publication

Towards a Multi-agents Approach for Understanding Speech

1996
Reports

Abstract

This paper describes a currently running project at IDIAP, aiming at the development of a continuous spoken language recognition system. A particular attention is paid to two important topics under investigation. Firstly, the system characteristics, namely its structure as a multi-agent system and secondly, its search mechanism of a global solution as an optimisation procedure, are studied. As this project is definitely an undergoing research activity, many still important open questions have to be addressed. The major one, concerning a mathematical foundation for the resolution mechanism is covered in a section dedicated to further developments.

Official source

https://infoscience.epfl.ch/entities/publication/5f97b78b-b3c3-4a27-b250-b784b3bb24a6

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1996
Reports

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/5f97b78b-b3c3-4a27-b250-b784b3bb24a6

About this result

Related concepts (22)

Multi-agent system

A multi-agent system (MAS or "self-organized system") is a computerized system composed of multiple interacting intelligent agents. Multi-agent systems can solve problems that are difficult or impossible for an individual agent or a monolithic system to solve. Intelligence may include methodic, functional, procedural approaches, algorithmic search or reinforcement learning. Despite considerable overlap, a multi-agent system is not always the same as an agent-based model (ABM).

Intelligent agent

In artificial intelligence, an intelligent agent (IA) is an agent acting in an intelligent manner; It perceives its environment, takes actions autonomously in order to achieve goals, and may improve its performance with learning or acquiring knowledge. An intelligent agent may be simple or complex: A thermostat or other control system is considered an example of an intelligent agent, as is a human being, as is any system that meets the definition, such as a firm, a state, or a biome.

Agent-based model

An agent-based model (ABM) is a computational model for simulating the actions and interactions of autonomous agents (both individual or collective entities such as organizations or groups) in order to understand the behavior of a system and what governs its outcomes. It combines elements of game theory, complex systems, emergence, computational sociology, multi-agent systems, and evolutionary programming. Monte Carlo methods are used to understand the stochasticity of these models.

Related publications (3)

Towards a Multi-agents Approach for Understanding Speech

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