000 04043nam a22006135i 4500
001 978-3-031-61034-9
003 DE-He213
005 20251030112041.0
007 cr nn 008mamaa
008 240514s2024 sz | s |||| 0|eng d
020 _a9783031610349
_9978-3-031-61034-9
024 7 _a10.1007/978-3-031-61034-9
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
_2thema
245 1 0 _aMulti-Agent-Based Simulation XXIV
_h[electronic resource] :
_b24th International Workshop, MABS 2023, London, UK, May 29 – June 2, 2023, Revised Selected Papers /
_cedited by Luis G. Nardin, Sara Mehryar.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aX, 173 p. 61 illus., 44 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v14558
505 0 _a -- MABS Methodology and Tools. -- Can (and should) Automated Surrogate Modelling be Used for Simulation Assistance?. -- Towards a Better Understanding of Agent-Based Airport Terminal Operations using Surrogate Modeling. -- Active Sensing for Epidemic State Estimation using ABM-guided Machine Learning. -- Combining Constraint-Based and Imperative Programming in MABS for More Reliable Modelling. -- Multi-Agent Financial Systems with RL: A Pension Ecosystem Case (WIP). -- MABS and Social Behavior. -- Aspects of Modeling Human Behavior in Agent-Based Social Simulation – What can We Learn from the COVID-19 Pandemic?. -- Learning Agent Goal Structures by Evolution. -- Dynamic Context-Sensitive Deliberation. -- MABS Applications. -- A Multi-Agent Simulation Model considering the Bounded Rationality of Market Participants: An Example of GENCOs Participation in the Electricity Spot Market. -- Modeling Cognitive Workload in Open-Source Communities via Simulation. -- Multi-Agent Simulation of Intelligent Resource Regulation in Integrated Energy and Mobility.
520 _aThis book constitutes the refereed Proceedings of the 24th International Workshop on Multi-Agent-Based Simulation XXIV, MABS 2023, held in London, UK, during May 29–June 2, 2023. The 11 regular papers presented were carefully reviewed and selected from 27 submissions. The papers are organized in subject areas as follows: MABS methodology and tools; MABS and social behavior; and MABS applications.
650 0 _aArtificial intelligence.
_958441
650 0 _aSocial sciences
_xData processing.
_965741
650 0 _aApplication software.
650 0 _aEducation
_xData processing.
650 0 _aComputer networks .
_960157
650 1 4 _aArtificial Intelligence.
_958441
650 2 4 _aComputer Application in Social and Behavioral Sciences.
_965743
650 2 4 _aComputer and Information Systems Applications.
650 2 4 _aComputers and Education.
650 2 4 _aComputer Communication Networks.
_965689
700 1 _aNardin, Luis G.
_eeditor.
_0(orcid)0000-0002-4506-2745
_1https://orcid.org/0000-0002-4506-2745
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_976807
700 1 _aMehryar, Sara.
_eeditor.
_0(orcid)0000-0002-5755-0869
_1https://orcid.org/0000-0002-5755-0869
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_976808
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031610332
776 0 8 _iPrinted edition:
_z9783031610356
830 0 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v14558
856 4 0 _uhttps://doi.org/10.1007/978-3-031-61034-9
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
912 _aZDB-2-LNC
999 _c59851
_d59851