CS344M Autonomous Multiagent Systems Patrick MacAlpine Department - - PowerPoint PPT Presentation

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CS344M Autonomous Multiagent Systems Patrick MacAlpine Department - - PowerPoint PPT Presentation

Mar 04, 2023 109 likes •593 views

CS344M Autonomous Multiagent Systems Patrick MacAlpine Department of Computer Science The University of Texas at Austin Good Afternoon, Colleagues Are there any questions? Patrick MacAlpine Good Afternoon, Colleagues Are there any

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CS344M Autonomous Multiagent Systems

Patrick MacAlpine Department of Computer Science The University of Texas at Austin

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Good Afternoon, Colleagues

Are there any questions?

Patrick MacAlpine

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Good Afternoon, Colleagues

Are there any questions?

  • Pending questions:

− How are agents like automatons? − What is episodic? − What is deterministic? − Set theory in states/actions? − Is a pencil an agent?

Patrick MacAlpine

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Logistics

  • First assignment: how did it go?

Patrick MacAlpine

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Logistics

  • First assignment: how did it go?
  • Next soccer assignment: score a goal

Patrick MacAlpine

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Logistics

  • First assignment: how did it go?
  • Next soccer assignment: score a goal

− Help each other with C issues — parsing strings

Patrick MacAlpine

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Logistics

  • First assignment: how did it go?
  • Next soccer assignment: score a goal

− Help each other with C issues — parsing strings − Evaluating mostly on the logic — does the agent “do the right thing?”

Patrick MacAlpine

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Logistics

  • First assignment: how did it go?
  • Next soccer assignment: score a goal

− Help each other with C issues — parsing strings − Evaluating mostly on the logic — does the agent “do the right thing?”

  • 2D or 3D?

Patrick MacAlpine

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Self-Introductions

  • Speak loudly

Patrick MacAlpine

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Self-Introductions

  • Speak loudly
  • Name, year, major

Patrick MacAlpine

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Self-Introductions

  • Speak loudly
  • Name, year, major
  • At least one other thing about yourself

Patrick MacAlpine

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Discussion

An autonomous agent is a system situated within and a part of an environment that senses that environment and acts on it, over time, in pursuit of its own agenda and so as to affect what it senses in the future.

  • Is this a good definition?
  • The authors claim is is a “formal” definition of agents. Is it?

Patrick MacAlpine

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Discussion

An autonomous agent is a system situated within and a part of an environment that senses that environment and acts on it, over time, in pursuit of its own agenda and so as to affect what it senses in the future.

  • Is this a good definition?
  • The authors claim is is a “formal” definition of agents. Is it?
  • Can you do better?

Patrick MacAlpine

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Discussion

An autonomous agent is a system situated within and a part of an environment that senses that environment and acts on it, over time, in pursuit of its own agenda and so as to affect what it senses in the future.

  • Is this a good definition?
  • The authors claim is is a “formal” definition of agents. Is it?
  • Can you do better?
  • Do they need to be social? persistent?
  • Can they cease to be agents in a different environment?
  • Autonomy

Patrick MacAlpine

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Varieties of Autonomy

  • Do we have complete freedom over our beliefs, goals,

and actions?

Patrick MacAlpine

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Varieties of Autonomy

  • Do we have complete freedom over our beliefs, goals,

and actions?

  • Software service has no autonomy — does what it’s told.

Patrick MacAlpine

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Varieties of Autonomy

  • Do we have complete freedom over our beliefs, goals,

and actions?

  • Software service has no autonomy — does what it’s told.
  • What’s Wooldridge’s take on where autonomous agents

lie on the spectrum?

Patrick MacAlpine

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Varieties of Autonomy

  • Do we have complete freedom over our beliefs, goals,

and actions?

  • Software service has no autonomy — does what it’s told.
  • What’s Wooldridge’s take on where autonomous agents

lie on the spectrum? − Decide how to act so as to accomplish delegated goals

Patrick MacAlpine

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Varieties of Autonomy

  • Do we have complete freedom over our beliefs, goals,

and actions?

  • Software service has no autonomy — does what it’s told.
  • What’s Wooldridge’s take on where autonomous agents

lie on the spectrum? − Decide how to act so as to accomplish delegated goals

  • Also mentions adjustable autonomy

Patrick MacAlpine

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My Requirements of Agents

  • They must sense their environment.
  • They must decide what action to take (“think”).
  • They must act in their environment.

Patrick MacAlpine

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My Requirements of Agents

  • They must sense their environment.
  • They must decide what action to take (“think”).
  • They must act in their environment.

Complete Agents

Patrick MacAlpine

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My Requirements of Agents

  • They must sense their environment.
  • They must decide what action to take (“think”).
  • They must act in their environment.

Complete Agents Multiagent systems: Interact with other agents

Patrick MacAlpine

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My Requirements of Agents

  • They must sense their environment.
  • They must decide what action to take (“think”).
  • They must act in their environment.

Complete Agents Multiagent systems: Interact with other agents Learning agents: Improve performance from experience

Patrick MacAlpine

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My Requirements of Agents

  • They must sense their environment.
  • They must decide what action to take (“think”).
  • They must act in their environment.

Complete Agents Multiagent systems: Interact with other agents Learning agents: Improve performance from experience Autonomous Bidding, Cognitive Systems, Traffic management, Robot Soccer

Patrick MacAlpine

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Environments

Environment = ⇒ sensations, actions

Patrick MacAlpine

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Environments

Environment = ⇒ sensations, actions

  • fully observable vs. partially observable (accessible)

Patrick MacAlpine

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Environments

Environment = ⇒ sensations, actions

  • fully observable vs. partially observable (accessible)
  • deterministic vs. non-deterministic

Patrick MacAlpine

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Environments

Environment = ⇒ sensations, actions

  • fully observable vs. partially observable (accessible)
  • deterministic vs. non-deterministic
  • episodic vs. non-episodic

Patrick MacAlpine

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Environments

Environment = ⇒ sensations, actions

  • fully observable vs. partially observable (accessible)
  • deterministic vs. non-deterministic
  • episodic vs. non-episodic
  • static vs. dynamic

Patrick MacAlpine

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Environments

Environment = ⇒ sensations, actions

  • fully observable vs. partially observable (accessible)
  • deterministic vs. non-deterministic
  • episodic vs. non-episodic
  • static vs. dynamic
  • discrete vs. continuous

Patrick MacAlpine

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Environments

Environment = ⇒ sensations, actions

  • fully observable vs. partially observable (accessible)
  • deterministic vs. non-deterministic
  • episodic vs. non-episodic
  • static vs. dynamic
  • discrete vs. continuous
  • single-agent vs. multiagent

Patrick MacAlpine

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The Decision

Patrick MacAlpine

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The Decision

  • reactive vs. deliberative

Patrick MacAlpine

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The Decision

  • reactive vs. deliberative
  • multiagent reasoning?

Patrick MacAlpine

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The Decision

  • reactive vs. deliberative
  • multiagent reasoning?
  • learning?

Patrick MacAlpine

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Formalizing My Example

Knowns:

  • O = {Blue, Red, Green, Black, . . .}
  • Rewards in IR
  • A = {Wave, Clap, Stand}
  • 0, a0, r0, o1, a1, r1, o2, . . .

Unknowns:

  • S = 4x3 grid
  • R : S × A → IR
  • P = S → O
  • T : S × A → S
  • i = P(si)

ri = R(si, ai) si+1 = T (si, ai)

Patrick MacAlpine

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Standard/Reactive/State-based Agents

  • Standard agent:

Patrick MacAlpine

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Standard/Reactive/State-based Agents

  • Standard agent:

action : P∗ → A

Patrick MacAlpine

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Standard/Reactive/State-based Agents

  • Standard agent:

action : P∗ → A

  • Reactive agent:

Patrick MacAlpine

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Standard/Reactive/State-based Agents

  • Standard agent:

action : P∗ → A

  • Reactive agent:

action : P → A

Patrick MacAlpine

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Standard/Reactive/State-based Agents

  • Standard agent:

action : P∗ → A

  • Reactive agent:

action : P → A − Decision based entirely on the present

Patrick MacAlpine

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Standard/Reactive/State-based Agents

  • Standard agent:

action : P∗ → A

  • Reactive agent:

action : P → A − Decision based entirely on the present

  • State-based agent:

Patrick MacAlpine

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Standard/Reactive/State-based Agents

  • Standard agent:

action : P∗ → A

  • Reactive agent:

action : P → A − Decision based entirely on the present

  • State-based agent:

action : I → A, next : I × P → I

Patrick MacAlpine

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Standard/Reactive/State-based Agents

  • Standard agent:

action : P∗ → A

  • Reactive agent:

action : P → A − Decision based entirely on the present

  • State-based agent:

action : I → A, next : I × P → I It is worth observing that state-based agents as defined here are in fact no more powerful than the standard agents we introduced earlier. In fact, they are identical in their expressive power.

Patrick MacAlpine

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Standard/Reactive/State-based Agents

  • Standard agent:

action : P∗ → A

  • Reactive agent:

action : P → A − Decision based entirely on the present

  • State-based agent:

action : I → A, next : I × P → I It is worth observing that state-based agents as defined here are in fact no more powerful than the standard agents we introduced earlier. In fact, they are identical in their expressive power. Reactive agents for next Thursday’s assignment task?

Patrick MacAlpine

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Discussion

What are some tasks that are partially observable, non-deterministic, dynamic, continuous, and multi-agent?

Patrick MacAlpine

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Discussion

What are some tasks that are partially observable, non-deterministic, dynamic, continuous, and multi-agent? Can we possibly expect an agent to perform well in such tasks?

Patrick MacAlpine