This unit covers logical representation and planning. "Pushing against complexity":
- Complexity of the agent: start with simple reflex-based agents, move towards goal- and utility-based agents
- Complexity of the environment: start with simple environments, then look at partial observability, and stochastic actions, and multiple agents
- Complexity of the representation: the agent's model of the world becomes increasingly complex
|Type of Logic||Ontological Commitment||Epistemological Commitment|
|First Order Logic||Relations, Objects, Functions||True, False, Unknown|
|Propositional Logic||Facts||True, False, Unknown|
We can use inference mechanisms to determine the validity and satisfiability of propositions, but there are significant limitations of this framework.
- No capability to handle uncertainty
- Can only talk about events, not objects
- No shortcuts to talk about a lot of different things happening
First-order Logic. Two of the limitations of propositional logic are addressed by first-order logic (not uncertainty). The syntax of first-order logic is made up of sentences and terms which can be combined using the operators from propositional logic. In first-order logic the relations are about objects, but not relations. In higher-order logic there are relations about relations.
When the world is not fully observable and deterministic we have to adapt the plan (feedback control). Why do we have
- stochastic: we don't know exactly what will happen as a result of our actions
- multi-agent: trying to predict what others are going to do
- partial observability: we can't know everything (we don't know exactly what state we're in)