Artificial Intelligence – Agent Behaviour by William John Teahan

artificial-intelligence-ageThe way an agent behaves is often used to tell them apart and to distinguish what and who they are, whether animal, human or artificial. Behaviour can also be associated with groups of agents, not just a single agent. For example, human cultural behaviour relates to behaviour that is associated with a particular nation, people or social group, and is distinct from the behaviour of an individual human being or the human body. Behaviour also has an important role to play in the survival of different species and subspecies. It has been suggested, for example, that music and art formed part of a suite of behaviours displayed by our own species that provided us with the evolutionary edge over the Neanderthals. In the two preceding chapters, Author has talked about various aspects concerning behaviours of embodied, situated agents, such as how an agent’s behaviour from a design perspective can be characterised in terms of its movement it exhibits in an environment, and how agents exhibit a range of behaviours from reactive to cognitive. Author has not, however, provided a more concrete definition of what behaviour is. From the perspective of designing embodied, situated agents, behaviour can be defined as follows. A particular behaviour of an embodied, situated agent is a series of actions it performs when interacting with an environment. The specific order or manner in which the actions’ movements are made and the overall outcome that occurs as a result of the actions defines the type of behaviour. We can define an action as a series of movements performed by an agent in relation to a specific outcome, either by volition (for cognitive-based actions) or by instinct (for reactive-based actions).


In this book the readers will read What is behaviour? Reactive versus Cognitive Agents, Emergence, Self-organization, Adaptivity and Evolution, The frame of Reference Problem, Stigmergy and Swarm Intelligence, Implementing behaviour of Turtle Agents in Netlogo, Boids, Communication, Information and Language, The diversity of human language, Communication via communities of agents, Communicating Behaviour, The Small World Phenomenon and Dijkstra’s algorithm, Using communicating agents for searching networks, Entropy and Information, Calculating Entropy in NetLogo, Language Modeling, Entropy of Language, Communicating Meaning, Search Behaviour, Search Problems, Uninformed (blind) search, Implementing uninformed search in NetLogo, Search as behaviour selection, Informed search, Local search and optimization, Comparing the search behaviours, Summary and Discussion, Knowledge and Knowledge-based systems, Knowledge as justified true belief, Different types of knowledge, Some approaches to Knowledge Representation and AI, Knowledge engineering problems, Knowledge without representation, Representing knowledge using maps, Representing knowledge using event maps, Representing knowledge using rules and logic, Reasoning using rules and logic, Knowledge and reasoning using frames, Knowledge and reasoning using decision trees, Knowledge and reasoning using semantic networks, The nature of Intelligence, Intelligence without representation and reason, What AI can and can’t do, The need for design objectives for Artificial Intelligence, What are Good Objectives? Some Design Objectives for Artificial Intelligence, Towards believable agents, Towards computers with problem solving ability and much in this book.

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