AI class unit 7

These are my notes for unit 7 of the AI class.

Representation with Logic

Introduction

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Welcome back. So far we've talked about AI as managing complexity and uncertainty. We've seen how search can discover sequences of actions to solve problems. We've seen how probability theory can represent and reason with uncertainty. And we've seen how machine learning can be used to learn and improve.

AI is a big and dynamic field because we're pushing against complexity in at least three directions. First, in terms of agent design, we start with a simple reflex-based agent and move into goal-based and utility-based agents. Secondly, in terms of the complexity of the environment, we start with simple environments and then start looking at partial observability, at stochastic actions, at multiple agents, and so on. And finally, in terms of representation, the agent's model of the the world becomes increasingly complex.

In this unit we'll concentrate on that third aspect of representation, showing how the tools of logic can be used by an agent to better model the world.