SoftwareAgentCourse

logistics: the official course outline, assignment submissions, office hours will be posted on Brightspace.

objectives: after this course, students should be able to:

• build simple agents and multi-agent systems using basic AI concepts
• read and understand most of the research material in the field of software agents

books: this course uses a certain number of SoftwareAgentBooks.

outline: (the official course outline can be found on Brightspace) (see the week-by-week AgentOverview to see how we actually will proceed)

• AgentDefinition and overview
• AgentKnowledgeRepresentation
• AgentReasoning
• AgentAdaptability
• InterfaceAgents
• BeliefDesireIntention
• AgentCommunicationLanguage
• MultiAgentSystems
• AgentProgrammingParadigms
• AgentTrust
• Agent Patterns (see [2])
• AgentFrameworks and Architectures
• MobileAgents
• AgentApplications
• EthicsOfAutonomy

assignments:

• will most probably count for 50% of the final grade
• the number and nature of assignments will depend on the number of students enrolled.

• will count for the other 50% of the final grade.
• the project topics will depend on the number of students enrolled.

For their contribution, help...: (in chronological order of contribution) Ramiro Liscano, Olivier Boissier, Sanjay Chandrasekharan, Vladimir Tosic, Dwight Deugo, Tom Gray, Steve Marsh, Michael Weiss, Tony White, Andre Vellino, Neal Arthorne, Kevin Lam, Shawn Henry, Michael Floyd, Natalia Villanueva-Rosales, Romelia Plesa, Edgar Acosta, Parthy Chandrasekaran, Patrick Gavigan, Mohamed Zalat, Michael Vezina.