- Anything that can be viewed as perceiving its environment through sensors and acting upon that environment through its effectors to maximize progress towards its goals.
- PAGE (Percepts, Actions, Goals, Environment)
- Task-specific & specialized: well-defined goals and environment
- The notion of an agent is meant to be a tool for analyzing systems, not an absolute characterization that divides the world into agents and non-agents. Much like, e.g., object-oriented vs. imperative program design approaches.
Intelligent Agents and AI
- Human mind as network of thousands or millions of agents all working in parallel. To produce real artificial intelligence, this school holds, we should build computer systems that also contain many agents and systems for arbitrating among the agents' competing results.
- Distributed decision-making
and control - Challenges:
- Action selection: What next action
to choose - Conflict resolution
Agent Types
- We can split agent research into two main strands:
- Distributed Artificial Intelligence (DAI) –
Multi-Agent Systems (MAS) (1980 – 1990) - Much broader notion of "agent" (1990’s – present)
- interface, reactive, mobile, information
A Windshield Wiper Agent
How do we design a agent that can wipe the windshields when needed?
- Goals?
- Percepts ?
- Sensors?
- Effectors ?
- Actions ?
- Environment ?
Interacting Agents
Collision Avoidance Agent (CAA)
- Goals: Avoid running into obstacles
- Percepts: Obstacle distance, velocity, trajectory
- Sensors: Vision, proximity sensing
- Effectors: Steering Wheel, Accelerator, Brakes, Horn, Headlights
- Actions: Steer, speed up, brake, blow horn, signal (headlights)
- Environment: Freeway
Lane Keeping Agent (LKA)
• Goals: Stay in current lane
• Percepts: Lane center, lane boundaries
• Sensors: Vision
• Effectors: Steering Wheel, Accelerator, Brakes
• Actions: Steer, speed up, brake
• Environment: Freeway
Conflict Resolution by Action Selection Agents
• Override: CAA overrides LKA
• Arbitrate: if Obstacle is Close then CAA
else LKA
• Compromise: Choose action that satisfies both
agents
• Any combination of the above
• Challenges: Doing the right thing
The Right Thing = The Rational Action
- Rational Action: The action that maximizes the expected value of the performance measure given the percept sequence to date
- Rational = Best ?
- Rational = Optimal ?
- Rational = Omniscience ?
- Rational = Clairvoyant ?
- Rational = Successful ?
How is an Agent different from other software?
- Agents are autonomous, that is they act on behalf of the user
- Agents contain some level of intelligence, from fixed rules to learning engines that allow them to adapt to changes in the environment
- Agents don't only act reactively, but sometimes also proactively
- Agents have social ability, that is they communicate with the user, the system, and other agents as required
- Agents may also cooperate with other agents to carry out more complex tasks than they themselves can handle
- Agents may migrate from one system to another to access remote resources or even to meet other agents
Summary
- Intelligent Agents:
- Anything that can be viewed as perceiving its environment through sensors and acting upon that environment through its effectors to maximize progress towards its goals.
- PAGE (Percepts, Actions, Goals, Environment)
- Described as a Perception (sequence) to Action Mapping: f : P* ® A
- Using look-up-table, closed form, etc.
- Agent Types: Reflex, state-based, goal-based, utility-based
- Rational Action: The action that maximizes the expected value of the performance measure given the percept sequence to date
