View Proposal
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Proposer
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Ron Petrick
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Title
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Plan-based explainability in artificial intelligence systems
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Goal
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Description
- This project will explore the problem of explainability in AI systems (XAI) using automated planning tools (XAIP). Automated planners provide a causal model of states, actions, and plans which will serve as the underlying framework for explaining agent behaviour in particular circumstances. New approaches to plan explainability will be explored and implemented using existing planners that may be augmented and tested using representative planning domains.
- Resources
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Background
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Good knowledge of a programming language (e.g., C++, Python, or Java).
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Url
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Difficulty Level
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Moderate
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Ethical Approval
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None
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Number Of Students
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2
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Supervisor
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Ron Petrick
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Keywords
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Degrees
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Bachelor of Science in Computer Science
Bachelor of Science in Computer Systems
Master of Engineering in Software Engineering
Master of Science in Artificial Intelligence
Master of Science in Artificial Intelligence with SMI