Artificial Intelligence Terminology
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Terminology
- Intelligent Agent
- Interacts with environment
Sensors -> Control Policy -> Actuators = Perception Action Cycle
- Fully Observable
- Sufficient information to make optimal decision
- Partially Observable
- Memory required on agent - not all information available
- Deterministic
- Agents actions uniquely determine outcome
- Stochastic
- Outcomes include randomness - not wholly predicted by action e.g. dice game
- Discrete
- Finite number of sense/actions e.g. chess
- Continuous - Infinite number of sense/actions e.g. darts
- Benign
- No others have objective that is contra to your objective e.g. weather
- Adversal
- They are out to get you - e.g. Chess
| Activity | Fully Observable | Stocastic | Discrete | Adversal |
|---|---|---|---|---|
| Chess | Y | N (Determined by Agent + Opponent) | Y | Y |
| Poker | N | Y | Y | Y |
| Robotic car | N | Y | N | N (Not in Stanford) |
Rationality
Does the "right" thing given what it knows
Uncertainty management in software
What to do when you don't "know"
- Causes - Sensor limits, Adversary, Laziness (could compute - e.g. too expensive), Ignorant - could know but don't care to know
Problem Solving
- Initial state
- Action(State) -> {a1, a2, a3...} - actions from set may be dependent on state
- Result(State, Action) -> S' - new state
- GoalTest(State) -> True/False - reached goal
- PathCost(S -a1-> S' -a2-> S''...) = n - cost of step, action combinations
- StepCost(S, a, S') = n - Most path costs can be considered additive thus this can be considered the sum of a StepCost
Admissible heuristics
heuristic must be optimistic
- h(s) < true cost
Problem solving requirements
- fully observable
- known domain - actions available
- discrete domain - finite
- deterministic
- static - nothing else changes world other than our actions
Turing Test
Requires:
- natural language processing
- knowledge representation
- automated reasoning
- machine learning
Full Turing test also:
- computer vision
- robotics
Syllogisms
- logical reasoned arguments
Logic solving systems exist but modelling a problem 100% logic and resources required are limiting factors in using this