Deep Learning – COSC2779 – Modelling Sequential (Time Series) Data Deep Learning – COSC2779 Modelling Sequential (Time Series) Data Dr. Ruwan Tennakoon Sep 6, 2021 Reference: Chapter 10: Ian Goodfellow et. al., “Deep Learning”, MIT Press, 2016. Lecture 7 (Part 1) Deep Learning – COSC2779 Sep 6, 2021 1 / 39 MAIA – AI for […]
# pacmanAgents.py # ————— # Licensing Information: Please do not distribute or publish solutions to this # project. You are free to use and extend these projects for educational # purposes. The Pacman AI projects were developed at UC Berkeley, primarily by # John DeNero ( .edu) and Dan Klein ( .edu). # For more
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Deep Learning – COSC2779 – Deep Feed Forward Networks Deep Learning – COSC2779 Deep Feed Forward Networks Dr. Ruwan Tennakoon July 26, 2021 Reference: Chapter 6: Ian Goodfellow et. al., “Deep Learning”, MIT Press, 2016. Lecture 2 (Part 1) Deep Learning – COSC2779 July 26, 2021 1 / 46 Outline Part 1: Deep Feed Forward
Basics of PROLOG c©Hector Levesque CPS721: Artificial Intelligence Acknowledgement: based on the slides prepared by Hector Levesque September 14, 2021 CPS721: Artificial Intelligence (CS/RU) Basics of PROLOG September 14, 2021 1 / 15 Prolog in perspective PROLOG = PROgramming in LOGic, i.e., declarative, non-imperative programming. Radically different concept of programming from “conventional” computer languages: Computation
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# textDisplay.py # ————– # Licensing Information: Please do not distribute or publish solutions to this # project. You are free to use and extend these projects for educational # purposes. The Pacman AI projects were developed at UC Berkeley, primarily by # John DeNero ( .edu) and Dan Klein ( .edu). # For more
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PowerPoint Presentation CSE 3521: Adversarial Search [Many slides are adapted from the UC Berkeley. CS188 Intro to AI at UC Berkeley and previous CSE 3521 course at OSU.] Game Playing Agents Build an agent to play: Tic-Tac-Toe Checkers Chess Go Poker For centuries used by humans to exert intelligence Recent success in building game programs
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# projectParams.py # —————- # Licensing Information: You are free to use or extend these projects for # educational purposes provided that (1) you do not distribute or publish # solutions, (2) you retain this notice, and (3) you provide clear # attribution to UC Berkeley, including a link to http://ai.berkeley.edu. # # Attribution Information:
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# eightpuzzle.py # ————– # Licensing Information: Please do not distribute or publish solutions to this # project. You are free to use and extend these projects for educational # purposes. The Pacman AI projects were developed at UC Berkeley, primarily by # John DeNero ( .edu) and Dan Klein ( .edu). # For more
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PowerPoint Presentation CSE 3521: Search [Many slides are adapted from the UC Berkeley. CS188 Intro to AI at UC Berkeley and previous CSE 3521 course at OSU.] Recap: State space graphs vs. search trees S a b d p a c e p h f r q q c G a q e p h
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# pacman.py # ——— # Licensing Information: Please do not distribute or publish solutions to this # project. You are free to use and extend these projects for educational # purposes. The Pacman AI projects were developed at UC Berkeley, primarily by # John DeNero ( .edu) and Dan Klein ( .edu). # For more
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