Here - Agents Lab - University of Nottingham

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OrganisationOrganising CommitteeMehdi DastaniBrian LoganJomi F. HübnerUtrecht University, The NetherlandsUniversity of Nottingham, UKFederal University of Santa Catarina, BrazilSteering CommitteeRafael H. BordiniMehdi DastaniJuergen DixAmal E.F. SeghrouchniFederal University of Rio Grande do Sul, BrazilUtrecht University, NetherlandsClausthal University of Technology, GermanyUniversity of Paris VI, France)Program CommitteeNatasha AlechinaLacramioara AstefanoaeiMatteo BaldoniOlivier BoissierJuan Botia BlayaLars BraubachRem CollierLouise DennisVladimir GorodetskyFrancisco GrimaldoJames HarlandKoen HindriksBenjamin HirschMax KnobboutJoao LeiteViviana MascardiPhilippe MathieuJohn-Jules MeyerJorg MullerPeter NovkAlexander PokahrUniversity of Nottingham, UKLaboratoire d’Informatique de Grenoble, FranceUniversity of Torino, ItalyEcole des Mines de St Etienne, FranceUniversity of Murcia, SpainUniversity of Hamburg, GermanyUniversity College Dublin, IrelandUniversity of Liverpool, UKRussian Academy of Sciences, RussiaUniversitat de ValenciaRMIT, AustraliaDelft University of Technology, The NetherlandsTechnical University of Berlin, GermanyUtrecht University, The NetherlandsUniversity Nova de Lisboa, PortugalGenova University, ItalyUniv. Lille 1, FranceUtrecht University, The NetherlandsClausthal University of Technology, GermanyCzech Technical University, Czech RepublicUniversity of Hamburg, Germany
Alessandro RicciBirna van RiemsdijkRalph RonnquistSebastian SardinaIchiro SatohMichael Ignaz SchumacherKostas StathisBas SteunebrinkJohn ThangarajahPankaj TelangWamberto VasconcelosJrgen VilladsenNeil Yorke-SmithYingqian ZhangUniversity of Bologna, ItalyDelft University of Technology, The NetherlandsIntendico, AustraliaRMIT University, AustraliaNII, JapanUniversity of Applied Sciences Western Switzerland,Sierre, SwitzerlandRoyal Holloway, University of London, UKUniversity of Lugano, SwitzerlandRMIT, AustraliaCiscoUniversity of Aberdeen, UKDTU Informatics, DenmarkAmerican University of Beirut, Lebanon and SRIInternational, USADelft University of Technology, The NetherlandsAdditional ReviewersAntonn KomendaMatthias KnorrAndrea Santi
Page 2 and 3: Proceedings of the Tenth Internatio
Page 6: Table of ContentseJason: an impleme
Page 10 and 11: in Sect. 3 the translation of the J
Page 12 and 13: init_count(0).max_count(2000).(a)(b
Page 14 and 15: For instance, a failure in the ERES
Page 16 and 17: {plan, fun start_count_trigger/1,fu
Page 18 and 19: single parameter, an Erlang record
Page 20 and 21: 1. Belief annotations. Even though
Page 22 and 23: decisions taken during the design a
Page 24 and 25: Conceptual Integration of Agents wi
Page 26 and 27: Fig. 2. Active component structurep
Page 28 and 29: the service provider component. As
Page 30 and 31: Fig. 4. Web Service Invocationretri
Page 32 and 33: 01: public interface IBankingServic
Page 34 and 35: tate them in the same way as in the
Page 36 and 37: 01: public interface IChartService
Page 38 and 39: implementations being available for
Page 41: deliberative behavior in BDI archit
Page 44 and 45: layer modules (i.e. nodes) can be d
Page 46 and 47: different methods to choose the cur
Page 48 and 49: also a single scheduler module, imp
Page 50 and 51: andom choice (OR), conditional choi
Page 52 and 53: - Dealing with conflicts based on p
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5. Brooks, R. A. (1991) Intelligenc
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An Agent-Based Cognitive Robot Arch
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It has been argued that building ro
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EnvironmentHardwareLocal SoftwareC+
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a cognitive layer can connect as a
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can reliably be differentiated and
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4 ExperimentTo evaluate the feasibi
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learn or gain knowledge from experi
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A Programming Framework for Multi-A
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exchange and storage of tuples (key
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Although some success [13] [14] hav
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as well as important non-functional
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component plans have been instantia
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A in the example) can evaluate all
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1. robot-1 issues a Localization(ro
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ACKNOWLEDGMENTThis work has been su
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The code was analysed both objectiv
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a conversation is following. Additi
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the context of a communication-heav
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Table 1. Core Agent ProtocolsAgent
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statistically significant using an
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to the conversation and has a perfo
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principal reasons. Firstly, it is a
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2. Muldoon, C., O’Hare, G.M.P., C
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In the following section we will at
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DevelopmentProductionHuman Readabil
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will then evaluate this new format
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encoder, it is first checked if the
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nents themselves. However, since th
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optimized for this format feature s
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Java serialization and Jadex Binary
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10. P. Hoffman and F. Yergeau, “U
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Caching the results of previous que
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querying an agent’s beliefs and g
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or relative performance of each pla
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were run for 1.5 minutes; 1.5 minut
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Size N K n p c qry U c upd Update c
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epresentation. The cache simply act
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6 ConclusionWe presented an abstrac
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Typing Multi-Agent Programs in simp
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1 // agent ag02 iterations (" zero
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3.1 simpAL OverviewThe main inspira
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3.2 Typing Agents with Tasks and Ro
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Defining Agent Scripts in simpAL (F
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that sends a message to the receive
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* error: wrong type for the param v
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Given an organization model, it is
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Learning to Improve Agent Behaviour
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2.1 Agent Programming LanguagesAgen
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choosing actions is to find a good
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1 init module {2 knowledge{3 block(
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of a module. For example, to change
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if bel(on(X,Y), clear(X)), a-goal(c
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mance. Figure 2d shows the same A f
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the current percepts of the agent.
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Author IndexAbdel-Naby, S., 69Alelc
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