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The Nature of Statistical Learning Theory

by Vladimir N. Vapnik , 1999
"... Statistical learning theory was introduced in the late 1960’s. Until the 1990’s it was a purely theoretical analysis of the problem of function estimation from a given collection of data. In the middle of the 1990’s new types of learning algorithms (called support vector machines) based on the deve ..."
Abstract - Cited by 13236 (32 self) - Add to MetaCart
on the developed theory were proposed. This made statistical learning theory not only a tool for the theoretical analysis but also a tool for creating practical algorithms for estimating multidimensional functions. This article presents a very general overview of statistical learning theory including both

Maximum likelihood from incomplete data via the EM algorithm

by A. P. Dempster, N. M. Laird, D. B. Rubin - JOURNAL OF THE ROYAL STATISTICAL SOCIETY, SERIES B , 1977
"... A broadly applicable algorithm for computing maximum likelihood estimates from incomplete data is presented at various levels of generality. Theory showing the monotone behaviour of the likelihood and convergence of the algorithm is derived. Many examples are sketched, including missing value situat ..."
Abstract - Cited by 11972 (17 self) - Add to MetaCart
A broadly applicable algorithm for computing maximum likelihood estimates from incomplete data is presented at various levels of generality. Theory showing the monotone behaviour of the likelihood and convergence of the algorithm is derived. Many examples are sketched, including missing value

Flocking for Multi-Agent Dynamic Systems: Algorithms and Theory

by Reza Olfati-Saber , 2006
"... In this paper, we present a theoretical framework for design and analysis of distributed flocking algorithms. Two cases of flocking in free-space and presence of multiple obstacles are considered. We present three flocking algorithms: two for free-flocking and one for constrained flocking. A compre ..."
Abstract - Cited by 436 (2 self) - Add to MetaCart
In this paper, we present a theoretical framework for design and analysis of distributed flocking algorithms. Two cases of flocking in free-space and presence of multiple obstacles are considered. We present three flocking algorithms: two for free-flocking and one for constrained flocking. A

Consensus and cooperation in networked multi-agent systems

by Reza Olfati-Saber , J Alex Fax , Richard M Murray , Reza Olfati-Saber , J Alex Fax , Richard M Murray - Proceedings of the IEEE , 2007
"... Summary. This paper provides a theoretical framework for analysis of consensus algorithms for multi-agent networked systems with an emphasis on the role of directed information flow, robustness to changes in network topology due to link/node failures, time-delays, and performance guarantees. An ove ..."
Abstract - Cited by 807 (4 self) - Add to MetaCart
Summary. This paper provides a theoretical framework for analysis of consensus algorithms for multi-agent networked systems with an emphasis on the role of directed information flow, robustness to changes in network topology due to link/node failures, time-delays, and performance guarantees

Markov games as a framework for multi-agent reinforcement learning

by Michael L. Littman - IN PROCEEDINGS OF THE ELEVENTH INTERNATIONAL CONFERENCE ON MACHINE LEARNING , 1994
"... In the Markov decision process (MDP) formalization of reinforcement learning, a single adaptive agent interacts with an environment defined by a probabilistic transition function. In this solipsistic view, secondary agents can only be part of the environment and are therefore fixed in their behavior ..."
Abstract - Cited by 601 (13 self) - Add to MetaCart
In the Markov decision process (MDP) formalization of reinforcement learning, a single adaptive agent interacts with an environment defined by a probabilistic transition function. In this solipsistic view, secondary agents can only be part of the environment and are therefore fixed

Consensus Seeking in Multi-agent Systems under Dynamically Changing Interaction Topologies

by Wei Ren, Randal W. Beard , 2003
"... This note considers the problem of information consensus among multiple agents in the presence of limited and unreliable information exchange with dynamically changing interaction topologies. Both discrete and continuous update schemes are proposed for information consensus. The note shows that i ..."
Abstract - Cited by 449 (37 self) - Add to MetaCart
that information consensus under dynamically changing interaction topologies can be achieved asymptotically if the union of the directed interaction graphs across some time intervals has a spanning tree frequently enough as the system evolves. Simulation results show the effectiveness of our update schemes.

Developing multi-agent systems with JADE

by Fabio Bellifemine, Agostino Poggi, Giovanni Rimassa - Wiley Series in Agent Technology , 2007
"... Abstract. JADE (Java Agent Development Framework) is a software framework to make easy the development of multi-agent applications in compliance with the FIPA specifications. JADE can then be considered a middle-ware that implements an efficient agent platform and supports the development of multi a ..."
Abstract - Cited by 320 (5 self) - Add to MetaCart
Abstract. JADE (Java Agent Development Framework) is a software framework to make easy the development of multi-agent applications in compliance with the FIPA specifications. JADE can then be considered a middle-ware that implements an efficient agent platform and supports the development of multi

A Methodology for Agent-Oriented Analysis and Design

by Michael Wooldridge , Nicholas R. Jennings, David Kinny , 1999
"... This paper presents a methodology for agent-oriented analysis and design. The methodology is general, in that it is applicable to a wide range of multi-agent systems, and comprehensive, in that it deals with both the macro-level (societal) and the micro-level (agent) aspects of systems. The methodol ..."
Abstract - Cited by 829 (12 self) - Add to MetaCart
This paper presents a methodology for agent-oriented analysis and design. The methodology is general, in that it is applicable to a wide range of multi-agent systems, and comprehensive, in that it deals with both the macro-level (societal) and the micro-level (agent) aspects of systems

Multiobjective evolutionary algorithms: a comparative case study and the strength pareto approach

by Eckart Zitzler, Lothar Thiele - IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION , 1999
"... Evolutionary algorithms (EA’s) are often well-suited for optimization problems involving several, often conflicting objectives. Since 1985, various evolutionary approaches to multiobjective optimization have been developed that are capable of searching for multiple solutions concurrently in a singl ..."
Abstract - Cited by 813 (22 self) - Add to MetaCart
Evolutionary algorithms (EA’s) are often well-suited for optimization problems involving several, often conflicting objectives. Since 1985, various evolutionary approaches to multiobjective optimization have been developed that are capable of searching for multiple solutions concurrently in a

Is it an Agent, or just a Program?: A Taxonomy for Autonomous Agents

by Stan Franklin, Art Graesser - In Intelligent Agents III , 1997
"... The advent of software agents gave rise to much discussion of just what such an agent is, and of how they differ from programs in general. Here we propose a formal definition of an autonomous agent which clearly distinguishes a software agent from just any program. We also offer the beginnings of a ..."
Abstract - Cited by 788 (51 self) - Add to MetaCart
The advent of software agents gave rise to much discussion of just what such an agent is, and of how they differ from programs in general. Here we propose a formal definition of an autonomous agent which clearly distinguishes a software agent from just any program. We also offer the beginnings of a
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