AI Approaches Overview

AI Approaches Overview:

The following subsections provide brief overviews of five separate AI approaches:

1. Approach A - PDDL / Classical Planning
2. Approach B - Value Iteration
3. Approach C - Approximate Q-Learning
4. Approach D - A* Heuristic Search
5. Approach E - Behaviour Trees

Within each of these different approaches, we discuss our motivation for investigating the approach; the general theory behind the AI method; the trade-offs involved. Most approaches were explicitly used in developing an agent(s); some were not explicitly utilised, but instead inspired some aspect of an agent(s) development; and one approach was investigated but failed to be implemented due to various reasons (discussed in PDDL / Classical Planning).

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