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CM50206: Intelligent agents

[Page last updated: 27 October 2020]

Follow this link for further information on academic years Academic Year: 2020/1
Further information on owning departmentsOwning Department/School: Department of Computer Science
Further information on credits Credits: 6      [equivalent to 12 CATS credits]
Further information on notional study hours Notional Study Hours: 120
Further information on unit levels Level: Masters UG & PG (FHEQ level 7)
Further information on teaching periods Period:
Semester 1
Further information on unit assessment Assessment Summary: CW 60%, EX 40%
Further information on unit assessment Assessment Detail:
  • Coursework 1 (CW 40%)
  • Coursework 2 (CW 20%)
  • Examination (EX 40%)
Further information on supplementary assessment Supplementary Assessment:
Like-for-like reassessment (where allowed by programme regulations)
Further information on requisites Requisites:
Description: Aims:
To introduce students to the principles of agents, agency, institutions and agent software development.

Learning Outcomes:
Students will:
* know the factors that differentiate agents from other software systems;
* be able to classify agents according to their competencies;
* be able to describe and contrast different agent architectures, platforms and approaches to agent development;
* be able to develop simple agent-based software systems;
* have an understanding of the issues involved in designing, implementing and evaluating a multi-agent system;
* have an understanding of contemporary research issues in the area of multi-agent systems.

Skills:

* Understanding theoretical concepts required for agent-based systems (T, A);
* Ability to link theory and practice of multiagent systems (T, F, A);
* Ability to apply current agent-based technology (T, F,A).

Content:

* Theory and practice of (multi-) agency. Selected topics from: logic, reasoning, negotiation, game theory, argumentation, institutions and norms, auctions, agent architectures, agent platforms, standards, ontologies and communication and content languages, decision making, trust and reputation;
* Case studies of practical applications;
* Discussion of research in the area of MAS.
Further information on programme availabilityProgramme availability:

CM50206 is Optional on the following programmes:

Department of Computer Science
  • RSCM-AFM51 : Integrated PhD Accountable, Responsible and Transparent Artificial Intelligence
  • TSCM-AFM51 : MRes Accountable, Responsible and Transparent Artificial Intelligence
  • TSCM-AFM52 : MSc Accountable, Responsible and Transparent Artificial Intelligence
  • TSCM-AFM48 : MSc Machine Learning and Autonomous Systems
  • TSCM-AWM48 : MSc Machine Learning and Autonomous Systems
  • TSCM-AFM21 : MSc Software Systems
  • TSCM-AWM35 : MSc Software Systems
  • USCM-AFM01 : MComp(Hons) Computer Science (Year 4)
  • USCM-AAM02 : MComp(Hons) Computer Science with Study year abroad (Year 5)
  • USCM-AKM02 : MComp(Hons) Computer Science with Year long work placement (Year 5)
  • USCM-AFM14 : MComp(Hons) Computer Science and Mathematics (Year 4)
  • USCM-AAM14 : MComp(Hons) Computer Science and Mathematics with Study year abroad (Year 5)
  • USCM-AKM14 : MComp(Hons) Computer Science and Mathematics with Year long work placement (Year 5)
Department of Electronic & Electrical Engineering

Notes:

  • This unit catalogue is applicable for the 2020/21 academic year only. Students continuing their studies into 2021/22 and beyond should not assume that this unit will be available in future years in the format displayed here for 2020/21.
  • Programmes and units are subject to change in accordance with normal University procedures.
  • Availability of units will be subject to constraints such as staff availability, minimum and maximum group sizes, and timetabling factors as well as a student's ability to meet any pre-requisite rules.
  • Find out more about these and other important University terms and conditions here.