Artificial Intelligence: Foundations of Computational Agents,  3rd Edition

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Part I Agents in the World
What are Agents and How Can They be Built?

1. 1 Artificial Intelligence and Agents

1. 2 Agent Architectures and Hierarchical Control

Part II Reasoning and Planning with Certainty
How can an agent represent its knowledge, reason, and plan, under the assumption that it knows both what is true in the world and the effects of its actions?

1. 3 Searching for Solutions

1. 4 Reasoning with Constraints

1. 5 Propositions and Inference

1. 6 Deterministic Planning

Part III Learning and Reasoning with Uncertainty
How can an agent learn and reason, relaxing the assumption that it knows what is in the world?

1. 7 Supervised Machine Learning

1. 8 Neural Networks and Deep Learning

1. 9 Reasoning with Uncertainty

1. 10 Learning with Uncertainty

1. 11 Causality

Part IV Planning and Acting with Uncertainty
How can an agent plan and act, relaxing the assumption that it knows the effects of its actions and the current state of the world?

1. 12 Planning with Uncertainty

1. 13 Reinforcement Learning

1. 14 Multiagent Systems

Part V Representing Individuals and Relations
How can an agent reason, learn, and act in more complex environments where there are individuals (things, entities, objects) with complex relations among them?

1. 15 Individuals and Relations

1. 16 Knowledge Graphs and Ontologies

1. 17 Relational Learning and Probabilistic Reasoning

Part VI The Big Picture
What are the social impacts of AI, and what are the likely future scenarios for AI science and technology?

1. 18 The Social Impact of Artificial Intelligence

1. 19 Retrospect and Prospect

Part VII End Matter

1. A Mathematical Preliminaries and Notation

1. B Mapping to Open-Source Packages

1. References

1. Index