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AI Planning for Autonomy (COMP90054)

Graduate courseworkPoints: 12.5On Campus (Parkville)

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Overview

Availability
Semester 1
Semester 2
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AIMS

The key focus of this subject is the foundations of autonomous agents that reason about action, applying techniques such as automated planning, reinforcement learning, game theory, and their real-world applications. Autonomous agents are active entities that perceive their environment, reason, plan and execute appropriate actions to achieve their goals, in service of their users (the real world, human beings, or other agents). The subject focuses on the foundations that enable agents to reason autonomously about goals & rewards, perception, actions, strategy, and the knowledge of other agents during collaborative task execution, and the ethical impacts of agents with this ability.

The programming language used in this subject is Python. No lectures or workshops on Python will be delivered.

INDICATIVE CONTENT

Topics are drawn from the field of advanced artificial intelligence including:

  • Search algorithms and heuristic functions
  • Classical (AI) planning
  • Markov Decision Processes
  • Reinforcement learning
  • Game theory
  • Ethics in AI planning

Intended learning outcomes

On completion of this subject the student is expected to:

  • Apply theoretical concepts of reasoning about actions to single and multi-agent problems
  • Be able to analyse, design, and implement automated planning, reinforcement learning, and game theoretic techniques to given problems
  • Understand the strengths, weaknesses, and ethical consequences of different approaches for reasoning about action
  • Be able to critically evaluate and choose the right technique for different problems in reasoning about action
  • Communicate technical solutions about automated planning, reinforcement learning, and game theory

Generic skills

On completion of the subject the students should have the following skills:

  • Ability to undertake problem identification, formulation, and solution
  • Ability to utilise a systems approach to complex problems and to design and operational performance
  • Ability to manage information and documentation
  • Capacity for creativity and innovation ability to communicate effectively with both the engineering team and the community at large

Last updated: 8 April 2024