Probability Collectives A Distributed Multi-agent System Approach for Optimization
Kulkarni, Anand Jayant.
Probability Collectives A Distributed Multi-agent System Approach for Optimization by Anand Jayant Kulkarni, Kang Tai, Ajith Abraham. - 1 recurso en línea (IX, 157 páginas 68 ilustraciones) - Intelligent Systems Reference Library, 86 1868-4394 ; Engineering (Springer-11647) .
Introduction to Optimization -- Probability Collectives: A Distributed Optimization Approach -- Constrained Probability Collectives: A Heuristic Approach -- Constrained Probability Collectives with a Penalty Function Approach -- Constrained Probability Collectives With Feasibility-Based Rule I -- Probability Collectives for Discrete and Mixed Variable Problems -- Probability Collectives with Feasibility-Based Rule II.
This book provides an emerging computational intelligence tool in the framework of collective intelligence for modeling and controlling distributed multi-agent systems referred to as Probability Collectives. In the modified Probability Collectives methodology a number of constraint handling techniques are incorporated, which also reduces the computational complexity and improved the convergence and efficiency. Numerous examples and real world problems are used for illustration, which may also allow the reader to gain further insight into the associated concepts.
9783319160009
10.1007/978-3-319-16000-9 doi
Agentes inteligentes (Programas de ordenador)
QA76.76.I58 / K855 2015 EB
Probability Collectives A Distributed Multi-agent System Approach for Optimization by Anand Jayant Kulkarni, Kang Tai, Ajith Abraham. - 1 recurso en línea (IX, 157 páginas 68 ilustraciones) - Intelligent Systems Reference Library, 86 1868-4394 ; Engineering (Springer-11647) .
Introduction to Optimization -- Probability Collectives: A Distributed Optimization Approach -- Constrained Probability Collectives: A Heuristic Approach -- Constrained Probability Collectives with a Penalty Function Approach -- Constrained Probability Collectives With Feasibility-Based Rule I -- Probability Collectives for Discrete and Mixed Variable Problems -- Probability Collectives with Feasibility-Based Rule II.
This book provides an emerging computational intelligence tool in the framework of collective intelligence for modeling and controlling distributed multi-agent systems referred to as Probability Collectives. In the modified Probability Collectives methodology a number of constraint handling techniques are incorporated, which also reduces the computational complexity and improved the convergence and efficiency. Numerous examples and real world problems are used for illustration, which may also allow the reader to gain further insight into the associated concepts.
9783319160009
10.1007/978-3-319-16000-9 doi
Agentes inteligentes (Programas de ordenador)
QA76.76.I58 / K855 2015 EB