AI
- Rational Agents
  - Environments
  - Planning
  - Types of Agents
  - Action
  - Agent Architecture
  - Agent Function
  - AI as Rational Agents
  - Autonomy
  - Belief State
  - Bellman Equation
  - Effect
  - Environment
  - Offline Problem Solving
  - Online Problem Solving
  - Optimal Policy
  - PEAS
  - Percept
  - Performance Measure
  - Precondition
  - Rational Behavior
  - Sensor Markov Property
  - Sensor Model
  - Transition Function
  - Transition Model
  - Transition Relation
- Rational Non-Deterministic Agents
- Types of AI
- Artificial Intelligence
- Cognitive Science
Bayesian
Complexity Theory
Constraint Satisfaction Problem
Cryptography
Data Science
Decision Theory
Distances
Fourier Transform
Frequent Item
Graph
Information Theory
Knowledge Representation
Logic
Markov
Mathematics
media
Optimization
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Pattern Recognition
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INDEX
MOC - Introduction to Statistics and Statistical Programming
MOC - Stochastische Modellbildung

Transition Model

A function that assigns to any Action $a\in \mathcal{A}$ and a state $s\in \mathcal{S}$ a set of successor states (here into the set of all possible state combinations Potenzmenge).

\mathcal{T}: \mathcal{A} \times \mathcal{S} \rightarrow \mathcal{P}(\mathcal{S})

Updates the Belief State based on an Action.