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Knowledge-based system and multi-agent environment - Coggle Diagram
Knowledge-based system and multi-agent environment
Knowledge-based
A structured collection of information and facts about the world, used by AI systems to make decisions and solve problems.
Logical Agents
Need a knowledge base
Pathfinding agents limited
Reasoning Based on Internal representations of knowledge
Humans do not just react reflexively
Web Links
https://www.javatpoint.com/agent-environment-in-ai
https://www.geeksforgeeks.org/ai-the-wumpus-world-description/
https://www.javatpoint.com/knowledge-based-agent-in-ai
https://www.techtarget.com/searchenterprisedesktop/definition/cellular-automaton
Multi-agent environment
Multi-agent environments involve multiple agents interacting with each other and the environment, each having their own goals and capabilities.
Agents can collaborate or compete.
Agents may share information.
Necessary for achieving shared goals.
Complexity is higher due to multiple agents.
Examples:
Autonomous vehicle fleets, robotic soccer, online auctions.
Wumpus World
The Wumpus world is a simple world example to illustrate the worth of a knowledge-based agent and to represent knowledge representation. It was inspired by a video game Hunt the Wumpus by Gregory Yob in 1973.
The agent knows only its local perceptions in the Wumpus World.
The outcome of each action is precisely specified.
Actions are performed in a sequence, affecting future decisions.
The Wumpus and pits remain in fixed positions.
The environment consists of distinct, separate locations.
Emergence
Individuals follow simple rules
Macro-level phenomenon
Pattern of behavior
Emergent complexity
Collective Intelligence
Collective intelligence is the enhanced capability of a system to gather and analyze inputs from multiple sources to make decisions or provide responses.
Ex:
Siri uses data from many users to improve its accuracy and personalize interactions
Conway's Game of life
Conway's Game of Life is a cellular automaton featuring a grid where cells live, die, or are born according to their neighbors. Basic rules produce intricate patterns over multiple iterations.
Rules
Any live cell with fewer than two live neighbours dies, as if caused by underpopulation.
Any live cell with two or three live neighbours lives on to the next generation.
Any live cell with more than three live neighbours dies, as if by overpopulation.
Any dead cell with exactly three live neighbours becomes a live cell, as if by reproduction.
Craig Reynolds-boids
Craig Reynolds' Boids is a simulation model that replicates the flocking behavior of birds.
Rules
separation: steer to avoid crowding local flockmates
alignment: steer towards the average heading of local flockmates
cohesion: steer to move towards the average position (center of mass) of local flockmates
Cellular Automata
A cellular automaton (CA) comprises cells organized in a predetermined grid shape. Each cell undergoes state changes over time based on a set of rules determined by the states of neighboring cells.
ALIFE
Artificial life (ALife or A-Life) is an area of investigation in which scientists explore phenomena akin to those found in natural life, including its mechanisms and evolutionary dynamics, using computer simulations, robotics, and biochemistry experiments.
Knowledge - based agent
Knowledge-based agents are intelligent systems that utilize a repository of information to make informed choices, employing perception, reasoning, and action guided by stored knowledge and logical deductions.
An agent is capable of inferring the internal model of the environment.
An agent can determine suitable courses of action.
An agent must be capable of representing states, actions, and other elements.
An agent has the ability to integrate new sensory inputs.
An agent is capable of revising its internal model of the environment.