人工智能执行指南

William John Teahan William John Teahan Artificial Intelligence –Agent Behaviour I Artificial Intelligence – Agent Behaviour I1stedition© 2014 William John Teahan & bookboon.comISBN 978-87-7681-559-2 Contents Part 2 Agent Behaviour I8 6Behaviour9 6.1What is behaviour?106.2Reactive versus Cognitive Agents116.3Emergence, Self-organisation, Adaptivity and Evolution136.4The Frame of Reference Problem206.5Stigmergy and Swarm Intelligence226.6Implementing behaviour of Turtle Agents in NetLogo246.7Boids366.8Summary52 Communication54 77.1Communication, Information and Language557.2The diversity of human language567.3Communication via communities of agents607.4Communicating Behaviour63 Our peer groups are carefully tailored to members’EXPERIENCETHE VALUE OF APROFESSIONAL NETWORKEXPERIENCE THEBUSINESS BENEFITS OFA PROFESSIONAL NETWORK profiles, which ensures both adequate input fromprofessionals who match your level of managementand discipline, and avoids accidental placement witha group of competitors or significant customers.EGN acts as a support network for your entire business,giving you benefits that include upskilling of your keyemployees, insights into the latest market trends and tools. 7.5The Small World Phenomenon and Dijkstra’s algorithm677.6Using communicating agents for searching networks757.7Entropy and Information817.8Calculating Entropy in NetLogo827.9Language Modelling887.10Entropy of a Language907.11Communicating Meaning967.12Summary102 8.1Search Behaviour1048.2Search Problems1068.3Uninformed (blind) search1098.4Implementing uninformed search in NetLogo1178.5Search as behaviour selection1248.6Informed search1278.7Local search and optimisation1358.8Comparing the search behaviours1398.9Summary and Discussion144 This is a global network, wherethe return on human capital istruly enormous. PETER Y. B. TAYFOUNDER & CEOTPS CORPOR ATE SERVICES PTE LTD,SING APORE 9Knowledge1479.1Knowledge and Knowledge-based Systems1479.2Knowledge as justified true belief1519.3Different types of knowledge1539.4Some approaches to Knowledge Representation and AI1569.5Knowledge engineering problems1639.6Knowledge without representation1649.7Representing knowledge using maps1669.8Representing knowledge using event maps1719.9Representing knowledge using rules and logic1759.10Reasoning using rules and logic1829.11Knowledge and reasoning using frames1959.12Knowledge and reasoning using decision trees2039.13Knowledge and reasoning using semantic networks2069.14Summary and Discussion211 It is a great way to shareexperiences across differentkinds of companies. PATRICK LYKKEG A ARDSERVICE DELIVERY MANAGERMAERSK TANKERSEGN DENMARK 10Intelligence21310.1The nature of intelligence21310.2Intelligence without representation and reason21710.3What AI can and can’t do21810.4The Need for Design Objectives for Artificial Intelligence22410.5What are Good Objectives?22510.6Some Design Objectives for Artificial Intelligence22510.7Towards believable agents23210.8Towards computers with problem solving ability23910.9Summary and Discussion246 I find it so insightful co-creatingsolutions and having debateson the key questions, we have. VERONICA CABED OHR CONSULTANT & COACHEGN BELGIUM Part 2Agent Behaviour I 6Behaviour 1.Perspective issue: We have to distinguish between the perspective of the observer and theperspective of the agent itself. In particular, descriptions of behavior from an observer’sperspective must not be taken as the internal mechanisms underlying the describedbehavior.2.Behavior-versus-mechanism issue: The behavior of an agent is always the result ofa system-environment interaction. It cannot be explained on the basis of internalmechanisms only.3.Complexity issue: The complexity we observe in a particular behavior does not always indicateaccurately the complexity of the underlying mechanisms. Rolf Pfeifer and Christian Scheier. 2001.Understanding Intelligence. Page 112. The MIT Press. Part 1 of this volume has explored agents and environments and important aspects of agent-environment interaction,including movement, and embodiment, and how it affects behaviour. Part 2 explores agent behaviour, including differenttypes of behaviour such as communication, searching, knowing (knowledge) and intelligence. This chapter explores the topic of agent behaviour in more depth.The chapter is organised as follows. Section 6.1 providesa definition of behaviour. Section 6.2 revisits the distinction between reactive versus cognitive agents from a behaviouralperspective. Sections 6.3 to 6.5 describe useful concepts related to behaviour: emergence, self-organisation, adaptivity,evolution, the frame of reference problem, stigmergy, and swarm intelligence. Section 6.6 looks at how we can implementvarious types of behaviour using turtle agents in NetLogo. One particular method called boids is discussed in Section 6.7. 6.1What is behaviour? The way an agent behaves is often used to tell them apart and to distinguish what and who t