agent

Agent - PDF document

Aug 22, 2023 •316 likes •386 views

  1. ❴ ❪ ❪ ❪ ✦ ❪ ➼ ➅ ✦ ❪ ❪ ❪ ❪ ❴ ❵ ❫ ❡ ❪ ❵ ❴ ❫ ❪ ❑ ❴ ❑ ❵ ❵ ❪ ❪ ❪ ➴ ❪ ❫ ❫ ❴ ❡ ➌ ❪ ❪ ❡ ❵ ❴ ❫ ❪ ❫ ❵ ➌ ❪ ❺ ❪ ❪ ❪ ❪ ❴ ❵ ❫ ❡ ❵ ❪ ❴ ❫ ❪ ❑ ❑ ❑ ✦ �✂✁☎✄✝✆✟✞✂✠☛✡✌☞✎✍✑✏✓✒✔✞✂✕✖✞✂✡✘✗✚✙✛✞✢✜✣✏✓✡✤✠☛✡✌✥ ✍✣✡❻✗✳✏✳✍✑❼❲✙✛✞✢✜✣✏❽✡✌✠✴✡❾✥ ✮✣▲◆▼✓❅❇❃❆✬❊★❀✵✩❖P★✫✪❨✵❂▼✳❃P▼✓◗❲✲❇▲❿❁❙✰✳▲❚▲❯❅✴★✷✪◆❁❄✲✴❃P▲◆▼✓❅❀❋❽★✭❉ ◗✳❉❆❋ ✧✩★✫✪✭✬✯✮✣✰✓✪✭✱✳✲✴★✫✵✷✶✹✸✻✺ ✼✾✽✿★❀✵❂❁❄❃❆❅❇★✫❅❈✶✹✸❊❉❆✶✭❋✔✶✹✸❊❉❍●✿❋■✶✫✸❊❉ ❏✭✺ ✧☎▲◆➀❽▲◆✲☎❖P★✫✪✭✵❂▼✳❃P▼✳◗❲✲✴▲❲✬❊▲✿❁✎➁❲▲◆▼➂➀✓✪✭✲✴✲✴★✫✵❇➃➄❁❙✰✓✪✭✵❇◗◆★❀✵ ✮✣▲◆▼✿✲✴✵❂▲✭❖✔❖P★✫✪✭✵❇▼✓❃P▼✳◗ ★✫✪✭✵❇▼✳❃❆▼✳◗➆✲❇▲❿❁❙✰✳▲❚▲❯❅❇★❈✪◆❁❄✲✴❃❆▲✭▼❽❅✩✲❇▲➆▲◆✱✳✲✴❃❆❱❿❃P➇❀★❈➈✉✪✭❁❄✲❇▲✭✵❂➃ ❑❻➅ ▲✭➉✓✲✴✱✓➉✳✲ ✮✣▲◆▼✿✲✴✵❂▲✭❖✔✱❘▲✭❖❆❃❆❁❄❃❆★✫❅✌✲✴✰✓✪✭✲☎❁❙✰✳▲❚▲❯❅✴★❈▲◆✱✳✲❇❃P❱❲✪✭❖✢✪◆❁❄✲✴❃P▲◆▼✓❅ ❖P★✫✪❨✵❂▼✳❃P▼✓◗ ★✫✪✭✵❇▼✳❃❆▼✳◗➆✲❇▲➆✱✓❖❆✪✹➃➋➊❻✪◆❁✎➁❯◗◆✪✭❱❲❱❿▲◆▼ ❑✩❳ ❑❻➅ ✮✣▲◆▼✿❩✭★❀✵❂◗◆★❀▼✓❁❄★ ▲✭✲❇★✷❅✴★❀❩◆★❀✵❂✪✭❖■✱✳✵❂▲◆➀✳❖P★❀❱➍❁❙✰✓✪✭✵❙✪✭❁❄✲❇★❀✵❇❃❆❅❇✲✴❃❆❁❀❅❀➎ ★✫❖❆✪✹➃◆★✫✬➄✵❇★❀➐✘✪✭✵❙✬ ❑❻➏ ✱✳✱❘▲✭✵❂✲✴➉✳▼✓❃P✲➒➃➓➈⑥▲◆✵✩✪◆❁❄✲✴❃❆❩✭★✷★❄✽✿✱✓❖P▲✭✵❙✪❨✲❇❃P▲◆▼ ❑❾➑ ▲❯❅❇❅❇❃P➀✳❃P❖P❃❆✲➒➃➂✲✴✰❽✪❨✲☎❅❇✲❇✪✭✲✴★✷▲◆▼✳❖P➃➋✱❽✪❨✵❂✲✴❃❆✪✭❖P❖P➃➂▲◆➀✓❅❇★❀✵❇❩❨✪❨➀✓❖P★ ❑❻➔ ▲❯❅❇❅❇❃P➀✳❖P★✷▼✓★❀★✫✬➋✲✴▲❲❖P★✫✪✭✵❇▼➂❱➆➉✳❖P✲❇❃P✱✳❖P★✷✲❇✪◆❅❂➁❯❅✩➐❻❃P✲❇✰→❅❇✪✭❱❲★ ❑❻➔ ❅✴★❀▼❽❅✴▲◆✵❂❅✎➣✻★❄↔❘★✫❁❄✲❇▲✭✵❙❅ ❬P❭P❭ ❛❝❜ ❫❄❞ ❢❝❫ ❞✴❣ ❤❆❜☛❵ ✐❝❵ ❥❝❤❝❤❆❦✹❧❨♠P♥ ♦❆♣ qsr✎t✉r ♠P✈ qs♣ q❆✇P①❆②❂③s④❨❡ ⑤❆❫ ①⑥④❨❴❍⑦✎❜ ⑧❍⑨✳⑩❇❡ ①❷❶❍❸P❸P❹ ❬P❭P↕ ❛❝❜ ❫❄❞ ❢❝❫ ❞✴❣ ❤❆❜☛❵ ✐❝❵ ❥❝❤❝❤❆❦✹❧❨♠P♥ ♦❆♣ qsr✎t✉r ♠P✈ qs♣ q❆✇P①❆②❂③s④❨❡ ⑤❆❫ ①⑥④❨❴❍⑦✎❜ ⑧❍⑨✳⑩❇❡ ①❷❶❍❸P❸P❹ ➙→➛➝➜✝➞✷➟✾➠✔➡➤➢➦➥✉➜✔➧✛➨➓➩➭➫❀➯✯➠✔➡➲➡➤➳■➛ ➜✿➷➬➛➦➮☛➳➸➱✻✃✿➜❊➡➲➜❊➛✔❐➄❒❾➜✳➠❽➱✭➛➝➷➬➛➝❮Ï❰Ð➱❨➳➸Ñ➶➥✉➜❊➡ ➵✂★✫❅❇✪✭➉✳✵❂▲✳❋➸✶✹➺◆➺◆➻✻✺ ★✫✪✭✵❇▼➄✲❇▲❿✱✓❖❆✪✹➃➓➊❻✪◆❁✎➁❯◗◆✪✭❱❲❱❿▲◆▼ Agent ❱❲❱❿★✫✬✳❃❆✪✭✲✴★✤✵❇★❀➐✘✪✭✵❂✬ ✶✫➾◆➾➆❃➚➈➝➐❻❃P▼ ❑❾➽ State Reward Action ✶✫➾◆➾✛❃➚➈➶❖P▲❯❅✴★ ❑✘➪ ➾✛➈➹▲✭✵✩✪❨❖P❖✢▲◆✲❇✰✳★❀✵✩❅❇✲❇✪✭✲✴★✫❅ Environment ➵✢✵❙✪❨❃❆▼✳★✫✬➄➀✿➃➓✱✳❖❆✪✻➃❚❃P▼✳◗➭✶✭❉➚➻✛❱❲❃P❖P❖P❃P▲◆▼→◗❯✪✭❱❿★✫❅❻✪✭◗❯✪❨❃❆▼✓❅✴✲✩❃P✲❇❅❇★❀❖➚➈ ▲✻➐✚✪✭✱✳✱✳✵❂▲✹✽✿❃P❱➓✪✭✲✴★❀❖P➃➋★✫➘❯➉✓✪✭❖■✲✴▲❲➀❘★✫❅✴✲❻✰✿➉✓❱❲✪✭▼➋✱✳❖❆✪✻➃◆★❀✵ a a a 0 1 2 s s s ... 0 1 2 r r r 0 1 2 Goal: Learn to choose actions that maximize 2 γ r + r + ... , where r + γ 0 < γ <1 0 1 2 ❬P❭P❹ ❛❝❜ ❫❄❞ ❢❝❫ ❞✴❣ ❤❆❜☛❵ ✐❝❵ ❥❝❤❝❤❆❦✹❧❨♠P♥ ♦❆♣ qsr✎t✉r ♠P✈ qs♣ q❆✇P①❆②❂③s④❨❡ ⑤❆❫ ①⑥④❨❴❍⑦✎❜ ⑧❍⑨✳⑩❇❡ ①❷❶❍❸P❸P❹ ❬P❭PÒ ❛❝❜ ❫❄❞ ❢❝❫ ❞✴❣ ❤❆❜☛❵ ✐❝❵ ❥❝❤❝❤❆❦✹❧❨♠P♥ ♦❆♣ qsr✎t✉r ♠P✈ qs♣ q❆✇P①❆②❂③s④❨❡ ⑤❆❫ ①⑥④❨❴❍⑦✎❜ ⑧❍⑨✳⑩❇❡ ①❷❶❍❸P❸P❹

Recommend

Overview Multi-Agent Systems Introduction to multi-agent systems and agent societies Agent

Overview Multi-Agent Systems Introduction to multi-agent systems and agent societies Agent

CPE/CSC 580-S06 Artificial Intelligence Intelligent Agents Overview Multi-Agent Systems Introduction to multi-agent systems and agent societies Agent Communication knowledge exchange among agents Agent Interaction eliminates explicit

623 views • 26 slides
An Agent Architecture An Agent Architecture An Agent Architecture An Agent Architecture for

An Agent Architecture An Agent Architecture An Agent Architecture An Agent Architecture for

An Agent Architecture An Agent Architecture An Agent Architecture An Agent Architecture for Predicting Protein Secondary for Predicting Protein Secondary for Predicting Protein Secondary for Predicting Protein Secondary Structures

992 views • 65 slides
S S S S calable calable Agent calable calable Agent Agent Plat forms Agent Plat forms

S S S S calable calable Agent calable calable Agent Agent Plat forms Agent Plat forms

EGI CF 2015, BARI, Exploiting the EGI Federated clouds, 11 Nov. 2015 S S S S calable calable Agent calable calable Agent Agent Plat forms Agent Plat forms lat forms wit h lat forms wit h wit h wit h friendly int eract ion friendly

319 views • 14 slides
Agent-Based Systems Agent communication Speech act theory Michael Rovatsos Agent

Agent-Based Systems Agent communication Speech act theory Michael Rovatsos Agent

Agent-Based Systems Agent-Based Systems Where are we? Last time . . . Agent-Based Systems Agent communication Speech act theory Michael Rovatsos Agent communication languages (KQML/KIF , FIPA-ACL) mrovatso@inf.ed.ac.uk

340 views • 5 slides
The Player Agent The Player Agent Are they the most important league official right now? right

The Player Agent The Player Agent Are they the most important league official right now? right

The Player Agent The Player Agent Are they the most important league official right now? right now? Player Agent Player Agent- post registration post registration The Player Agent following registration is the most important person in

280 views • 11 slides
Rational Agents (Ch. 2) Rational agent An agent/robot must be able to perceive and interact with

Rational Agents (Ch. 2) Rational agent An agent/robot must be able to perceive and interact with

Rational Agents (Ch. 2) Rational agent An agent/robot must be able to perceive and interact with the environment A rational agent is one that always takes the best action (possibly expected best) Agent = Rational agent Consider the case of a

535 views • 39 slides
Agent-Based Systems Michael Rovatsos mrovatso@inf.ed.ac.uk Lecture 6 Agent Communication 1

Agent-Based Systems Michael Rovatsos mrovatso@inf.ed.ac.uk Lecture 6 Agent Communication 1

Agent-Based Systems Agent-Based Systems Michael Rovatsos mrovatso@inf.ed.ac.uk Lecture 6 Agent Communication 1 / 25 Agent-Based Systems Where are we? Last time . . . Reactive and hybrid agent architectures Criticism of symbolic

622 views • 25 slides
Agent Training Welcome Blues Agent Portal Training e-Learning on the BCBSM Agent Portal

Agent Training Welcome Blues Agent Portal Training e-Learning on the BCBSM Agent Portal

Agent Training Welcome Blues Agent Portal Training e-Learning on the BCBSM Agent Portal Todays information is also available online via a new effort by the BCBSM Sales Force Development area. In the future look for online e-Learning modules

796 views • 67 slides
Multi-agent learning Multi-agent reinforcement learning Gerard Vreeswijk , Intelligent Systems

Multi-agent learning Multi-agent reinforcement learning Gerard Vreeswijk , Intelligent Systems

Multi-agent learning Multi-agent reinforcement learning Multi-agent learning Multi-agent reinforcement learning Gerard Vreeswijk , Intelligent Systems Group, Computer Science Department, Faculty of Sciences, Utrecht University, The Netherlands.

752 views • 21 slides
Agent-Based Systems Agent: autonomous Learning for Agent-Based Systems Environment: fully,

Agent-Based Systems Agent: autonomous Learning for Agent-Based Systems Environment: fully,

Agent-Based Systems Agent: autonomous Learning for Agent-Based Systems Environment: fully, partially, not observable S awomir Nowaczyk deterministic, stochastic, strategic actions static, dynamic, stationary, non-stationary episodic,

289 views • 15 slides
Agent-Based Systems Michael Rovatsos mrovatso@inf.ed.ac.uk Lecture 2 Abstract Agent

Agent-Based Systems Michael Rovatsos mrovatso@inf.ed.ac.uk Lecture 2 Abstract Agent

Agent-Based Systems Agent-Based Systems Michael Rovatsos mrovatso@inf.ed.ac.uk Lecture 2 Abstract Agent Architectures 1 / 16 Agent-Based Systems Where are we? Last time . . . Introduced basic and advanced aspects of agency

461 views • 16 slides
Learning Agent Learning Agents An Agent that observes its performance and adapts its

Learning Agent Learning Agents An Agent that observes its performance and adapts its

Learning Agent Learning Agents An Agent that observes its performance and adapts its decision-making to improve its performance in the future. MSE 2400 EaLiCaRA Dr. Tom Way MSE 2400 Evolution &amp; Learning 2 Agent Simple Reflex Agent

292 views • 4 slides
Chapter2 Intelligent Agents 2 20070308 chap2 1 20070308 chap2 What Is An Agent ?

Chapter2 Intelligent Agents 2 20070308 chap2 1 20070308 chap2 What Is An Agent ?

What Is An Agent ? Chapter2 Intelligent Agents 2 20070308 chap2 1 20070308 chap2 What Is An Agent ? (cont.-1) What Is An Agent ? (cont.-2) An agent interacts with its environments through Agent function (abstract mathematical

361 views • 7 slides
LECTURE 8: macro-aspects of intelligent agent technology: those issues relating to the Agent

LECTURE 8: macro-aspects of intelligent agent technology: those issues relating to the Agent

Agent Communication In this lecture and the next, we cover LECTURE 8: macro-aspects of intelligent agent technology: those issues relating to the Agent Communication agent society , rather than the individual: communication; speech acts;

324 views • 4 slides
Essential Ingredients for Building a Shared Agent Network DAVID PORTEOUS EFINA Agent Banking

Essential Ingredients for Building a Shared Agent Network DAVID PORTEOUS EFINA Agent Banking

Essential Ingredients for Building a Shared Agent Network DAVID PORTEOUS EFINA Agent Banking Breakfast Series 19 September 2013 Outline What is a shared agent network? Different models Pros and cons A way forward for scale in Nigeria? 2

284 views • 26 slides
FLUSSONIC AGENT Flussonic Agent is a camera software that extends default capabilities of

FLUSSONIC AGENT Flussonic Agent is a camera software that extends default capabilities of

FLUSSONIC AGENT Flussonic Agent is a camera software that extends default capabilities of Linux-based IP cameras Common IP camera problems: No plug-n-play Easy to hack No encryption Unstable video delivery, corrupted images Flussonic Agent

105 views • 8 slides
Tables, Priority Queues, Heaps Table ADT purpose, implementations Priority Queue ADT

Tables, Priority Queues, Heaps Table ADT purpose, implementations Priority Queue ADT

Tables, Priority Queues, Heaps Table ADT purpose, implementations Priority Queue ADT variation on Table ADT Heaps purpose, implementation heapsort EECS 268 Programming II 1 Table ADT A table in generic terms has M

1.03k views • 50 slides
ANOVA: Analysis of Variance Marc H. Mehlman marcmehlman@yahoo.com University of New Haven

ANOVA: Analysis of Variance Marc H. Mehlman marcmehlman@yahoo.com University of New Haven

ANOVA: Analysis of Variance Marc H. Mehlman marcmehlman@yahoo.com University of New Haven The analysis of variance is (not a mathematical theorem but) a simple method of arranging arithmetical facts so as to isolate and display the

632 views • 31 slides
Chapter Eleven: Non-Regular Languages Formal Language, chapter 11, slide 1 1 We have now

Chapter Eleven: Non-Regular Languages Formal Language, chapter 11, slide 1 1 We have now

Chapter Eleven: Non-Regular Languages Formal Language, chapter 11, slide 1 1 We have now encountered regular languages in several different places. They are the languages that can be recognized by a DFA. They are the languages that can be

873 views • 51 slides
SlideSet #11: Dynamic HTML (some from Chapter 9, 11,12 &amp;13 of book) Functions Recap

SlideSet #11: Dynamic HTML (some from Chapter 9, 11,12 &amp;13 of book) Functions Recap

IT350 Web and Internet Programming SlideSet #11: Dynamic HTML (some from Chapter 9, 11,12 &amp;13 of book) Functions Recap Whats the output? function fun1 (x) { x = x + 3; y = y + 4; document.writeln(&quot;&lt;br/&gt; FUN1: &quot;+x+

201 views • 6 slides
Chapter 13: I/O Systems I/O Hardware Application I/O Interface Kernel I/O Subsystem

Chapter 13: I/O Systems I/O Hardware Application I/O Interface Kernel I/O Subsystem

Chapter 13: I/O Systems I/O Hardware Application I/O Interface Kernel I/O Subsystem Transforming I/O Requests to Hardware Operations Streams Performance Operating System Concepts 13.1 Silberschatz, Galvin and Gagne

661 views • 31 slides
Motivations Chapter 13 Abstract Classes and You have learned how to write simple programs

Motivations Chapter 13 Abstract Classes and You have learned how to write simple programs

Motivations Chapter 13 Abstract Classes and You have learned how to write simple programs Interfaces to create and display GUI components. Can you write the code to respond to user actions, such as clicking a button to perform an action?

344 views • 10 slides
Chapter 13 Integration of Managing and the Arts Whats every day look like for an arts manager?

Chapter 13 Integration of Managing and the Arts Whats every day look like for an arts manager?

Chapter 13 Integration of Managing and the Arts Whats every day look like for an arts manager? Its preparing yourself for discontinuous activity interrupted by meetings The Plan? 1. Recognize whats really happening 2. Assessing

144 views • 13 slides
Software Quality Engineering: Testing, Quality Assurance, and Quantifiable Improvement Jeff

Software Quality Engineering: Testing, Quality Assurance, and Quantifiable Improvement Jeff

Slide (Ch.13) 1 Software Quality Engineering Software Quality Engineering: Testing, Quality Assurance, and Quantifiable Improvement Jeff Tian, tian@engr.smu.edu www.engr.smu.edu/ tian/SQEbook Chapter 13. Defect Prevention &amp; Process

710 views • 14 slides

More recommend