Logical Tree with its derived basic Thesaurus
010 ACM_is, Intelligent Systems
The field of artificial intelligence (AI) is concerned with the design
and analysis of autonomous agents These are software systems and/or physical
machines, with sensors and actuators, embodied for example within a robot
or an autonomous spacecraft An intelligent system has to perceive its
environment, to act rationally towards its assigned tasks, to interact
with other agents and with human beings These capabilities are covered
by topics such as computer vision, planning and acting, robotics, multiagents
systems, speech recognition, and natural language understanding They rely
on a broad set of general and specialized knowledge representations and
reasoning mechanisms, on problem solving and search algorithms, and on
machine learning techniques Furthermore, artificial intelligence provides
a set of tools for solving problems that are difficult or impractical
to solve with other methods These include heuristic search and planning
algorithms, formalisms for knowledge representation and reasoning, machine
learning techniques, and methods applicable to sensing and action problems
such as speech and language understanding, computer vision, and robotics,
among others The student needs to be able to determine when an AI approach
is appropriate for a given problem, and to be able to select and implement
a suitable AI method.
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Global Keywords
Intelligent systems, Search satisfaction, Constraint satisfaction, Knowledge representation, Knowledge reasoning, Agents, Intelligent agents, Natural language, Neural networks, AI, Artificial Intelligence, Robotics, Planning systems. |
010001 IS1, Fundamental issues in intelligent systems
Artificial, Intelligence, Philosophical, Questions, Definitions, Philosophical, Model, Heuristics.
010002 IS2, Search and constraint satisfaction
Space, Brute-force, Breadth-first, Depth-first, Depth-first, Iterative, Best-first, Search, Best-first, Dijkstra, Algorithm, A*, Two-player, Games, Alpha-beta, Backtracking, Method.
010003 IS3, Knowledge representation and reasoning
Propositional, Predicate, Logic, Theorem, Nonmonotonic, Probabilistic,
Bayes.
- 010003001 IS3, Review of propositional and predicate logic
Optimal vs, Vs, Human-like.
010004 IS4, Advanced search
Algorithms, Simulated, Annealing, Search.
010005 IS5, Advanced knowledge representation and reasoning
Structured, Nonmonotonic, Action, Change, Temporal, Spatial, Uncertainty, Diagnosis, Qualitative.
- 010005001 IS5, Structured representation
Frames, Objects, Logics, Inheritance, Systems.
- 010005002 IS5, Nonmonotonic reasoning
Nonclassical, Logics, Default, Knowledge, Sources, Aggregation, Conflicting, Belief.
- 010005003 IS5, Reasoning on action and change
Situation, Calculus, Event, Ramification, Problems.
- 010005004 IS5, Temporary and spatial reasoning
Temporary reasoning, Spatial reasoning.
- 010005005 IS5, Uncertainty
Probabilistic reasoning, Bayesian nets, Decision theory, Fuzzy sets.
- 010005006 IS5, Knowledge representation for diagnosis, qualitative representation
Knowledge representation, Qualitative representation, Knowledge diagnosis.
010006 IS6, Agents
Definition, Applications, State-of-the-art, Systems, Architectures, Theory, Software, Synthetic, Characters, Model, Emotions, Learning, Multi-agent, Robotic, Mobile.
- 010006003 IS6, Agent architectures
Reactive agents, Reactive planners, Layered architectures.
- 010006004 IS6, Agent theory
Agent commitments, Agent Intentions, Decision-theoretic agents, MDP, Markov, decision process.
- 010006005 IS6, Software agents, personal assistants, and information access
Collaborative agents, Information gathering agents, Gathering agents, Believable agents, Emotions modeling.
- 010006008 IS6, Multi-agent systems
Collaborating agents, Agent teams, Agent modeling, Multi agent learning.
010007 IS7, Natural language processing
Deterministic, Stochastic, Grammars, Parsing, Algorithms, Corpus-based,
Method, Information, Retrieval, Language, Translation, Speech.
010008 IS8, Machine learning and neural networks
Definition, Examples, Learning, Decision, Trees, Neural, Networks,
Algorithm, Learning theory, Overfitting, Unsupervised, Reinforcement.
010009 IS9, AI planning systems
Definition, Examples, Planning, Systems, Search, Operator-based, Propositional, Extending, Case-based, Probabilistic systems, Static world, Execution, Robotic.
010010 IS10, Robotics
Overview, Configuration, Space, Planning, Sensing, Robot, Programming, Navigation, Control.
- 010010001 IS10, Robotics overview
Robotics, Robot systems, Planning control, Reactive control, Control, Control uncertainty, Sensing, World models, Uncertainty, Navigation.
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