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Knowledge-based systems and multi-agent environments - Coggle Diagram
Knowledge-based systems and multi-agent environments
Agents
Knowledge Base
Declarative approach = tell it sentences
Procedural approach = encode in code
Sequence of actions
It tells knowledge base what it perceives MAKE PERCEPT SENTENCE
It asks knowledge base what action to perform MAKE ACTION QUERY
It tells knowledge base what action was chosen, then executes it MAKE ACTION SENTENCE
Logical agents
Pathfinding agents limited
Reasoning based on internal representations of knowledge
Humans - not just reflex reactions
Need a knowledge base
P.E.A.S.
Performance measure
+1000 if agents gets out with gold
-1000 if eaten by wumpus or falls into pit
-1 for every action
-10 for using arrow
Environment
4x4 grid
Agent at [1, 1]
Random gold and wumpus
0.2 probability of there being a bottomless pit
Actuators
Forward, turn left, turn right
Grab gold (if on same tile)
Shoot (arrow goes in direction agent is facing)
Climb out at [1, 1]
Sensors
SMELL Stench from adjacent squares to wumpus
FEEL Breeze from adjacent squares to pit
SEE Glitter from gold
FEEL Bump from wall
HEAR Scream from dead wumpus
Multi-agent environments
Planning - cooperation and coordination each agent makes its own plan
Convention
Communication
Collective intelligence
Decision-making in everything from bacteria to humans
Neural networks - adaptive systems - natural intelligence, not AI (rule-based learning)
Craig Reynolds - boids
Separation - avoid crowding (-ve)
Alignment - head in average direction (+ve)
Cohesion - steer towards average position (+ve)