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AIMA4e-NOTES--2022-11-23--03-32-35.pdf
(The below text version of the notes is for search purposes and convenience. See the PDF version for proper formatting such as bold, italics, etc., and graphics where applicable. Copyright: 2022 Retraice, Inc.)
AIMA4e Annotations
A companion to the great white brick.
As of November 23, 2022
(Start date: November 21, 2022.)
[1]retraice.com
Version notes: [2]Retraice ([3]2022/11/21) (Re57), first draft; [4]Retraice ([5]2022/11/22) (Re58), no footnotes; [6]Retraice ([7]2022/11/22) (Re58) again, moved some notes from Re57 and Re58 notes to footnotes here.
PREFACE
* The phenomenon: intelligent agents[8]^1 * The discipline: artificial intelligence,[9]^2 "the study of agents that receive percepts from the environment and perform actions." (vii)
* Aspects of the phenomenon: + Agent function: "Each ...agent implements a function that maps percept sequences to actions" (vii) o Ways to represent agent functions include: "reactive agents, real-time planners, decision-theoretic systems, and deep learning systems." (vii) + Learning o "a construction method for competent systems" (viii) o "a way of extending the reach of the designer into unknown environments." (viii) + Goals o Robotics and vision: # "not ...independently defined problems" # "[things] in the service of achieving goals."
I INTELLIGENCE --"Artificial Intelligence"
1 Intro:
definitions, foundations, history, philosophy, state of the art, risks-benefits
2 Agents:
environments, `good' behavior, agent structure and types
II SOLVING--"Problem-solving"
3 Searching: Looking ahead to find a sequence.
Algorithms, strategies, informed/heuristic[10]^3 strategies.
4 Complex Environments: More realistic environments.
Local search, optimization, continuous spaces, nondeterministic actions, partially observable env.s, online search and unknown env.s.
5 Adversarial Games: Other agents competing against us.
Theory, optimal decisions, alpha-beta tree search, Monte Carlo tree search, stochastic g.s, partially observable g.s, limitations.
6 Constraint Satisfaction Problems: States as domains, solutions as allowable combinations of states.
Constraint propagation, inference, backtracking search, local search, structure of problems
III THINKING--"Knowledge, reasoning, and planning"
7 Logical Agents: Forming representations and reasoning before acting.
Knowledge-based agents; representing[11]^4 worlds; logic, world models and `possible worlds';[12]^5 logic without objects.
8 First-Order Logic: A formal language for objects and their relations.
`Ontological commitment' (what is assumed about reality); syntax, semantics; knowledge engineering (building formal representations of important[13]^6 objects and relations in a domain).
9 First-Order Inference: Reasoning about objects and their relations.
Algorithms to answer any 1st-order logic question.
10 Knowledge Representation: Representing the real world for problem solving.
What content to put into a knowledge base.
Knowledge representation languages and their uses (315): * First-order logic: reasoning about a world of objects and relations; * Hierarchical task networks: for reasoning about plans (chpt. 11); * Bayesian networks: for reasoning with uncertainty (chpt. 13); * Markov models: for reasoning over time (chpt. 17); * Deep neural networks: for reasoning about images, sounds, other data (chpt. 21).
11 Automated Planning: Hierarchical task networks.
Planning for spacecraft, factories, military campaigns; representing actions and states; efficient algorithms and heuristics.
IV UNCERTAINTY--"Uncertain knowledge and reasoning"
12 Quantifying Uncertainty: An answer to the laziness and ignorance that kill formal logic.
Causes of uncertainty are environment types (partially observable,[14]^7 nondeterministic, adversarial[15]^8 ); belief state grows big and unlikely fast (384); agents still need a way to act; absolute certainty is impossible;[16]^9 it comes down to importance, likelihood and degree of success (385-386).
Logic fails because laziness and ignorance; probability theory solves the qualification problem by summarizing the uncertainty.[17]^10 * Laziness: too much work to list everything, or use such a list; * Ignorance: (theoretical) there are no complete theories; (practical) we can never run all the tests.
13 Probabilistic Reasoning [big]: Bayesian networks.
For reasoning with uncertainty by representing causal independence (398) and conditional independence (401) relationships to simplify probabilistic representations of the world.
14 Probabilistic Reasoning Over Time: Comprehending the uncertain past, present and future.
[18]^11
Belief state plus transition model yields prediction (chpt 4, 7, 11); percepts and sensor model yield updated belief state; add probability theory to switch from possible states to probable states.[19]^12
15 Probabilistic Programming: Universal formal languages to represent any computable probability model, and they come with algorithms.
Using formal logic and traditional programming languages to represent probabilistic information.
16 Making Simple Decisions: Agents getting what they want in an uncertain world--as much as possible, on average.
Beliefs, desires; utility theory; utility functions; decision networks; the value of information (547);[20]^13 this chapter is concerned with one-shot or episodic decisions problems (as opposed to sequential) (cf. 562, below).
17 Making Complex Decisions: What to do today given decisions to be made tomorrow.
Sequential decision problems (as opposed to one-shot episodic, cf. above): the agent's utility depends on a sequence of decisions in stochastic (explicitly probabilistic (45)) and partially observable environments. Markov models (563; cf. 463) for reasoning over time (chpt. 17).
18 Multiagent Decision Making [big]: When there's more than one agent in the environment.
The nature of such environments and the strategies for problem-solving depend on the relationships between agents: non-cooperative and cooperative game theory; collective decision-making.
V LEARNING--"Machine learning"
19: 20: 21: deep neural networks: for reasoning about images, sounds, other data (chpt. 21). 22:
VI INTERACTING--"Communicating, perceiving, and acting"
23: 24: 25: 26:
VII CONCLUSIONS--"Conclusions"
27: 28:
__
References
Crawford, K. (2021). Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. Yale University Press. ISBN: 978-0300209570. Searches: [21]https://www.amazon.com/s?k=9780300209570 [22]https://www.google.com/search?q=isbn+9780300209570 [23]https://lccn.loc.gov/2020947842
Frankfurt, H. G. (1988). The Importance of What We Care About. Cambridge. ISBN: 978-0521336116. Searches: [24]https://www.amazon.com/s?k=978-0521336116 [25]https://www.google.com/search?q=isbn+978-0521336116 [26]https://lccn.loc.gov/87026941
Kahneman, D. (2011). Thinking, Fast and Slow. Farrar, Straus and Giroux. ISBN: 978-0374533557. Searches: [27]https://www.amazon.com/s?k=978-0374533557 [28]https://www.google.com/search?q=isbn+978-0374533557 [29]https://lccn.loc.gov/2012533187
Retraice (2020/09/07). Re1: Three Kinds of Intelligence. retraice.com. [30]https://www.retraice.com/segments/re1 Retrieved 22nd Sep. 2020.
Retraice (2020/11/10). Re13: The Care Factor. retraice.com. [31]https://www.retraice.com/segments/re13 Retrieved 10th Nov. 2020.
Retraice (2020/11/25). Re15: Trust and Sources. retraice.com. [32]https://www.retraice.com/segments/re15 Retrieved 28th Feb. 2022.
Retraice (2022/10/19). Re23: You Need a World Model. retraice.com. [33]https://www.retraice.com/segments/re23 Retrieved 20th Oct. 2022.
Retraice (2022/10/23). Re27: Now That's a World Model - WM4. retraice.com. [34]https://www.retraice.com/segments/re27 Retrieved 24th Oct. 2022.
Retraice (2022/10/31). Re36: Notes on Conspiracy. retraice.com. [35]https://www.retraice.com/segments/re36 Retrieved 4th Nov. 2022.
Retraice (2022/11/12). Re48: From Drugs to Mao to Money. retraice.com. [36]https://www.retraice.com/segments/re48 Retrieved 14th Nov. 2022.
Retraice (2022/11/16). Re52: Big Questions About AI. retraice.com. [37]https://www.retraice.com/segments/re52 Retrieved 17th Nov. 2022.
Retraice (2022/11/21). Re57: AI, Agents, Problem-solving, Searching, Environments, Games (AIMA4e chpts. 1-6). retraice.com. [38]https://www.retraice.com/segments/re57 Retrieved 22nd Nov. 2022.
Retraice (2022/11/22). Re58: Thinking and Uncertainty (AIMA4e chpts. 7-18). retraice.com. [39]https://www.retraice.com/segments/re58 Retrieved 23rd Nov. 2022.
Russell, B. (1948). Human Knowledge: Its Scope and Limits. Routledge. First published in 1948. This edition 1992. ISBN: 0415083028. Searches: [40]https://archive.org/search.php?query=Human%20Knowledge%3A%20Its%20Scope%20and%20Limits [41]https://www.amazon.com/s?k=0415083028 [42]https://www.google.com/search?q=isbn+0415083028 [43]https://lccn.loc.gov/94209784
Vallee, J. (1979). Messengers of Deception: UFO Contacts and Cults. And/Or Press. ISBN: 0915904381. Different edition and searches: [44]https://archive.org/details/MessengersOfDeceptionUFOContactsAndCultsJacquesValle1979/mode/2up [45]https://www.amazon.com/s?k=0915904381 [46]https://www.google.com/search?q=isbn+0915904381 [47]https://catalog.loc.gov/vwebv/search?searchArg=0915904381
References
1. https://retraice.com/ 2. XReSeg57 3. XReSeg57 4. XReSeg58 5. XReSeg58 6. XReSeg58 7. XReSeg58 8. fn1x0 9. fn2x0 10. fn3x0 11. fn4x0 12. fn5x0 13. fn6x0 14. fn7x0 15. fn8x0 16. fn9x0 17. fn10x0 18. fn11x0 19. fn12x0 20. fn13x0 21. https://www.amazon.com/s?k=9780300209570 22. https://www.google.com/search?q=isbn+9780300209570 23. https://lccn.loc.gov/2020947842 24. https://www.amazon.com/s?k=978-0521336116 25. https://www.google.com/search?q=isbn+978-0521336116 26. https://lccn.loc.gov/87026941 27. https://www.amazon.com/s?k=978-0374533557 28. https://www.google.com/search?q=isbn+978-0374533557 29. https://lccn.loc.gov/2012533187 30. https://www.retraice.com/segments/re1 31. https://www.retraice.com/segments/re13 32. https://www.retraice.com/segments/re15 33. https://www.retraice.com/segments/re23 34. https://www.retraice.com/segments/re27 35. https://www.retraice.com/segments/re36 36. https://www.retraice.com/segments/re48 37. https://www.retraice.com/segments/re52 38. https://www.retraice.com/segments/re57 39. https://www.retraice.com/segments/re58 40. https://archive.org/search.php?query=Human%20Knowledge%3A%20Its%20Scope%20and%20Limits 41. https://www.amazon.com/s?k=0415083028 42. https://www.google.com/search?q=isbn+0415083028 43. https://lccn.loc.gov/94209784 44. https://archive.org/details/MessengersOfDeceptionUFOContactsAndCultsJacquesValle1979/mode/2up 45. https://www.amazon.com/s?k=0915904381 46. https://www.google.com/search?q=isbn+0915904381 47. https://catalog.loc.gov/vwebv/search?searchArg=0915904381
View all episodes
By Retraice, Inc.(The below text version of the notes is for search purposes and convenience. See the PDF version for proper formatting such as bold, italics, etc., and graphics where applicable. Copyright: 2022 Retraice, Inc.)
AIMA4e Annotations
A companion to the great white brick.
As of November 23, 2022
(Start date: November 21, 2022.)
[1]retraice.com
Version notes: [2]Retraice ([3]2022/11/21) (Re57), first draft; [4]Retraice ([5]2022/11/22) (Re58), no footnotes; [6]Retraice ([7]2022/11/22) (Re58) again, moved some notes from Re57 and Re58 notes to footnotes here.
PREFACE
* The phenomenon: intelligent agents[8]^1 * The discipline: artificial intelligence,[9]^2 "the study of agents that receive percepts from the environment and perform actions." (vii)
* Aspects of the phenomenon: + Agent function: "Each ...agent implements a function that maps percept sequences to actions" (vii) o Ways to represent agent functions include: "reactive agents, real-time planners, decision-theoretic systems, and deep learning systems." (vii) + Learning o "a construction method for competent systems" (viii) o "a way of extending the reach of the designer into unknown environments." (viii) + Goals o Robotics and vision: # "not ...independently defined problems" # "[things] in the service of achieving goals."
I INTELLIGENCE --"Artificial Intelligence"
1 Intro:
definitions, foundations, history, philosophy, state of the art, risks-benefits
2 Agents:
environments, `good' behavior, agent structure and types
II SOLVING--"Problem-solving"
3 Searching: Looking ahead to find a sequence.
Algorithms, strategies, informed/heuristic[10]^3 strategies.
4 Complex Environments: More realistic environments.
Local search, optimization, continuous spaces, nondeterministic actions, partially observable env.s, online search and unknown env.s.
5 Adversarial Games: Other agents competing against us.
Theory, optimal decisions, alpha-beta tree search, Monte Carlo tree search, stochastic g.s, partially observable g.s, limitations.
6 Constraint Satisfaction Problems: States as domains, solutions as allowable combinations of states.
Constraint propagation, inference, backtracking search, local search, structure of problems
III THINKING--"Knowledge, reasoning, and planning"
7 Logical Agents: Forming representations and reasoning before acting.
Knowledge-based agents; representing[11]^4 worlds; logic, world models and `possible worlds';[12]^5 logic without objects.
8 First-Order Logic: A formal language for objects and their relations.
`Ontological commitment' (what is assumed about reality); syntax, semantics; knowledge engineering (building formal representations of important[13]^6 objects and relations in a domain).
9 First-Order Inference: Reasoning about objects and their relations.
Algorithms to answer any 1st-order logic question.
10 Knowledge Representation: Representing the real world for problem solving.
What content to put into a knowledge base.
Knowledge representation languages and their uses (315): * First-order logic: reasoning about a world of objects and relations; * Hierarchical task networks: for reasoning about plans (chpt. 11); * Bayesian networks: for reasoning with uncertainty (chpt. 13); * Markov models: for reasoning over time (chpt. 17); * Deep neural networks: for reasoning about images, sounds, other data (chpt. 21).
11 Automated Planning: Hierarchical task networks.
Planning for spacecraft, factories, military campaigns; representing actions and states; efficient algorithms and heuristics.
IV UNCERTAINTY--"Uncertain knowledge and reasoning"
12 Quantifying Uncertainty: An answer to the laziness and ignorance that kill formal logic.
Causes of uncertainty are environment types (partially observable,[14]^7 nondeterministic, adversarial[15]^8 ); belief state grows big and unlikely fast (384); agents still need a way to act; absolute certainty is impossible;[16]^9 it comes down to importance, likelihood and degree of success (385-386).
Logic fails because laziness and ignorance; probability theory solves the qualification problem by summarizing the uncertainty.[17]^10 * Laziness: too much work to list everything, or use such a list; * Ignorance: (theoretical) there are no complete theories; (practical) we can never run all the tests.
13 Probabilistic Reasoning [big]: Bayesian networks.
For reasoning with uncertainty by representing causal independence (398) and conditional independence (401) relationships to simplify probabilistic representations of the world.
14 Probabilistic Reasoning Over Time: Comprehending the uncertain past, present and future.
[18]^11
Belief state plus transition model yields prediction (chpt 4, 7, 11); percepts and sensor model yield updated belief state; add probability theory to switch from possible states to probable states.[19]^12
15 Probabilistic Programming: Universal formal languages to represent any computable probability model, and they come with algorithms.
Using formal logic and traditional programming languages to represent probabilistic information.
16 Making Simple Decisions: Agents getting what they want in an uncertain world--as much as possible, on average.
Beliefs, desires; utility theory; utility functions; decision networks; the value of information (547);[20]^13 this chapter is concerned with one-shot or episodic decisions problems (as opposed to sequential) (cf. 562, below).
17 Making Complex Decisions: What to do today given decisions to be made tomorrow.
Sequential decision problems (as opposed to one-shot episodic, cf. above): the agent's utility depends on a sequence of decisions in stochastic (explicitly probabilistic (45)) and partially observable environments. Markov models (563; cf. 463) for reasoning over time (chpt. 17).
18 Multiagent Decision Making [big]: When there's more than one agent in the environment.
The nature of such environments and the strategies for problem-solving depend on the relationships between agents: non-cooperative and cooperative game theory; collective decision-making.
V LEARNING--"Machine learning"
19: 20: 21: deep neural networks: for reasoning about images, sounds, other data (chpt. 21). 22:
VI INTERACTING--"Communicating, perceiving, and acting"
23: 24: 25: 26:
VII CONCLUSIONS--"Conclusions"
27: 28:
__
References
Crawford, K. (2021). Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. Yale University Press. ISBN: 978-0300209570. Searches: [21]https://www.amazon.com/s?k=9780300209570 [22]https://www.google.com/search?q=isbn+9780300209570 [23]https://lccn.loc.gov/2020947842
Frankfurt, H. G. (1988). The Importance of What We Care About. Cambridge. ISBN: 978-0521336116. Searches: [24]https://www.amazon.com/s?k=978-0521336116 [25]https://www.google.com/search?q=isbn+978-0521336116 [26]https://lccn.loc.gov/87026941
Kahneman, D. (2011). Thinking, Fast and Slow. Farrar, Straus and Giroux. ISBN: 978-0374533557. Searches: [27]https://www.amazon.com/s?k=978-0374533557 [28]https://www.google.com/search?q=isbn+978-0374533557 [29]https://lccn.loc.gov/2012533187
Retraice (2020/09/07). Re1: Three Kinds of Intelligence. retraice.com. [30]https://www.retraice.com/segments/re1 Retrieved 22nd Sep. 2020.
Retraice (2020/11/10). Re13: The Care Factor. retraice.com. [31]https://www.retraice.com/segments/re13 Retrieved 10th Nov. 2020.
Retraice (2020/11/25). Re15: Trust and Sources. retraice.com. [32]https://www.retraice.com/segments/re15 Retrieved 28th Feb. 2022.
Retraice (2022/10/19). Re23: You Need a World Model. retraice.com. [33]https://www.retraice.com/segments/re23 Retrieved 20th Oct. 2022.
Retraice (2022/10/23). Re27: Now That's a World Model - WM4. retraice.com. [34]https://www.retraice.com/segments/re27 Retrieved 24th Oct. 2022.
Retraice (2022/10/31). Re36: Notes on Conspiracy. retraice.com. [35]https://www.retraice.com/segments/re36 Retrieved 4th Nov. 2022.
Retraice (2022/11/12). Re48: From Drugs to Mao to Money. retraice.com. [36]https://www.retraice.com/segments/re48 Retrieved 14th Nov. 2022.
Retraice (2022/11/16). Re52: Big Questions About AI. retraice.com. [37]https://www.retraice.com/segments/re52 Retrieved 17th Nov. 2022.
Retraice (2022/11/21). Re57: AI, Agents, Problem-solving, Searching, Environments, Games (AIMA4e chpts. 1-6). retraice.com. [38]https://www.retraice.com/segments/re57 Retrieved 22nd Nov. 2022.
Retraice (2022/11/22). Re58: Thinking and Uncertainty (AIMA4e chpts. 7-18). retraice.com. [39]https://www.retraice.com/segments/re58 Retrieved 23rd Nov. 2022.
Russell, B. (1948). Human Knowledge: Its Scope and Limits. Routledge. First published in 1948. This edition 1992. ISBN: 0415083028. Searches: [40]https://archive.org/search.php?query=Human%20Knowledge%3A%20Its%20Scope%20and%20Limits [41]https://www.amazon.com/s?k=0415083028 [42]https://www.google.com/search?q=isbn+0415083028 [43]https://lccn.loc.gov/94209784
Vallee, J. (1979). Messengers of Deception: UFO Contacts and Cults. And/Or Press. ISBN: 0915904381. Different edition and searches: [44]https://archive.org/details/MessengersOfDeceptionUFOContactsAndCultsJacquesValle1979/mode/2up [45]https://www.amazon.com/s?k=0915904381 [46]https://www.google.com/search?q=isbn+0915904381 [47]https://catalog.loc.gov/vwebv/search?searchArg=0915904381
References
1. https://retraice.com/ 2. XReSeg57 3. XReSeg57 4. XReSeg58 5. XReSeg58 6. XReSeg58 7. XReSeg58 8. fn1x0 9. fn2x0 10. fn3x0 11. fn4x0 12. fn5x0 13. fn6x0 14. fn7x0 15. fn8x0 16. fn9x0 17. fn10x0 18. fn11x0 19. fn12x0 20. fn13x0 21. https://www.amazon.com/s?k=9780300209570 22. https://www.google.com/search?q=isbn+9780300209570 23. https://lccn.loc.gov/2020947842 24. https://www.amazon.com/s?k=978-0521336116 25. https://www.google.com/search?q=isbn+978-0521336116 26. https://lccn.loc.gov/87026941 27. https://www.amazon.com/s?k=978-0374533557 28. https://www.google.com/search?q=isbn+978-0374533557 29. https://lccn.loc.gov/2012533187 30. https://www.retraice.com/segments/re1 31. https://www.retraice.com/segments/re13 32. https://www.retraice.com/segments/re15 33. https://www.retraice.com/segments/re23 34. https://www.retraice.com/segments/re27 35. https://www.retraice.com/segments/re36 36. https://www.retraice.com/segments/re48 37. https://www.retraice.com/segments/re52 38. https://www.retraice.com/segments/re57 39. https://www.retraice.com/segments/re58 40. https://archive.org/search.php?query=Human%20Knowledge%3A%20Its%20Scope%20and%20Limits 41. https://www.amazon.com/s?k=0415083028 42. https://www.google.com/search?q=isbn+0415083028 43. https://lccn.loc.gov/94209784 44. https://archive.org/details/MessengersOfDeceptionUFOContactsAndCultsJacquesValle1979/mode/2up 45. https://www.amazon.com/s?k=0915904381 46. https://www.google.com/search?q=isbn+0915904381 47. https://catalog.loc.gov/vwebv/search?searchArg=0915904381