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Natural Language Processing (History (Intelligent Agents(Percieve its…
Natural Language Processing
understanding
Linguistic
Computer science
History
Turing Test
Conceptual ontologies
Machine Learning Algorithms
Intelligent Agents(Percieve its environment through sensors and act accordingly with its effectors)
Depending Factors
Performance measures to determine degree of success
Perception sequence of agent
Agents prior knowledge about environment
the action which an agent can carry
Problem Solving Features
Performance
Environment
Actuators
Sensors
Structures
Agent =Architecture + Agent program
Architecture = the machinery that an agents compiles on
Agent program = an implementation of an agent function
Environment Properties
Deterministic and non-deterministic
Discrete/Continuous
Partial observable
Static and Dynamic
Single agent/ Multiple agent
Accessible/ Inaccessible
Types of Agents
Simple reflex agents
Model based reflex agents
Goal based agents
Utility based agents
Learning agents
features
Autonomy
Adaptability
Sociability
Applications
Pattern Recognition
Event Notification
Data Presentation
Optimization/Planning
Rapid response Implementation
Applications
Caption Generator
Question Answering
Voice recognition
Text Classification
Machine Translation
Challenges
Semantic Ambiguity
difficult to implement common sense
Unformatted questions
Lexical Ambiguity
Dialogues
Anaphoric Ambiguity
Good progress
Auto response
Grammatical analysis
Relevant answers