Interactions in Multiagent Systems: Fairness, Social Optimality and Individual Rationality

This book mainly aims at solving the problems in both cooperative and competitive multi-agent systems (MASs), exploring aspects such as how agents can effectively learn to achieve the shared optimal solution based on their local information and how they can learn to increase their individual utility...

Full description

Main Authors: Hao, Jianye. (Author, http://id.loc.gov/vocabulary/relators/aut), Leung, Ho-fung. (http://id.loc.gov/vocabulary/relators/aut)
Corporate Author: SpringerLink (Online service)
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2016.
Edition:1st ed. 2016.
Subjects:
Online Access:https://doi.org/10.1007/978-3-662-49470-7
LEADER 03339nam a22005295i 4500
001 978-3-662-49470-7
003 DE-He213
005 20210617114237.0
007 cr nn 008mamaa
008 160413s2016 gw | s |||| 0|eng d
020 |a 9783662494707  |9 978-3-662-49470-7 
024 7 |a 10.1007/978-3-662-49470-7  |2 doi 
050 4 |a Q342 
072 7 |a UYQ  |2 bicssc 
072 7 |a TEC009000  |2 bisacsh 
072 7 |a UYQ  |2 thema 
082 0 4 |a 006.3  |2 23 
100 1 |a Hao, Jianye.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Interactions in Multiagent Systems: Fairness, Social Optimality and Individual Rationality  |h [electronic resource] /  |c by Jianye Hao, Ho-fung Leung. 
250 |a 1st ed. 2016. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2016. 
300 |a IX, 178 p. 122 illus., 11 illus. in color.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
505 0 |a Introduction -- Background and Previous Work -- Fairness in Cooperative Multiagent Systems -- Social Optimality in Cooperative Multiagent Systems -- Individual Rationality in Competitive Multiagent Systems -- Social Optimality in Competitive Multiagent Systems -- Conclusion. 
520 |a This book mainly aims at solving the problems in both cooperative and competitive multi-agent systems (MASs), exploring aspects such as how agents can effectively learn to achieve the shared optimal solution based on their local information and how they can learn to increase their individual utility by exploiting the weakness of their opponents. The book describes fundamental and advanced techniques of how multi-agent systems can be engineered towards the goal of ensuring fairness, social optimality, and individual rationality; a wide range of further relevant topics are also covered both theoretically and experimentally. The book will be beneficial to researchers in the fields of multi-agent systems, game theory and artificial intelligence in general, as well as practitioners developing practical multi-agent systems. 
650 0 |a Computational intelligence. 
650 0 |a Artificial intelligence. 
650 0 |a Game theory. 
650 0 |a E-commerce. 
650 1 4 |a Computational Intelligence.  |0 https://scigraph.springernature.com/ontologies/product-market-codes/T11014 
650 2 4 |a Artificial Intelligence.  |0 https://scigraph.springernature.com/ontologies/product-market-codes/I21000 
650 2 4 |a Game Theory, Economics, Social and Behav. Sciences.  |0 https://scigraph.springernature.com/ontologies/product-market-codes/M13011 
650 2 4 |a e-Commerce/e-business.  |0 https://scigraph.springernature.com/ontologies/product-market-codes/I26000 
700 1 |a Leung, Ho-fung.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer Nature eBook 
776 0 8 |i Printed edition:  |z 9783662494684 
776 0 8 |i Printed edition:  |z 9783662494691 
776 0 8 |i Printed edition:  |z 9783662570128 
856 4 0 |u https://doi.org/10.1007/978-3-662-49470-7 
912 |a ZDB-2-ENG 
912 |a ZDB-2-SXE 
950 |a Engineering (SpringerNature-11647) 
950 |a Engineering (R0) (SpringerNature-43712)