No PCs! … IBM PC (1981) John McCarthy, Marvin Minsky, Allen...

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Year 1956, Dartmouth College No PCs! … IBM PC (1981)

John McCarthy, Marvin Minsky, Allen Newell

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Presenter
Presentation Notes
John McCarthy zorganizoval 1956 prvni konferenci o AI. Konference se zucastnil i Marvin Minsky, ktery se pripojil k nemu na MIT v Cambridgi a stal se jednim z evanglistu pocitacove UI, mimo jine se stal otcem umelych neuronovych sitich. A napriklad Alan Newell, ktery zavedl pojem “reasoning as search” … “premysleni jako prohledavani moznosti” February 10, 1996, Deep Blue porazi uradujiciho sachoveho velmistra Garry Kasparova, i kdyz lide Kasparovovi radili, aby hral “jako proti pocitaci”, nedbal toho. A practice match was recorded on January 13, 2011, and the official matches were recorded on January 14, 2011 Watson porazi Ken Jennings and Brad Rutter, two of the most successful contestants on the show.

Fully vs. Partially observable Episodic vs. Sequential Static vs. Dynamic Single vs. Multi agent Deterministic vs. Stochastic Discrete vs. Continuous Known vs. Unknown Turn-based vs. Real-time Noiseless vs. Noisy

Fully vs. Partially observable Episodic vs. Sequential Static vs. Dynamic Single vs. Multi agent Deterministic vs. Stochastic Discrete vs. Continuous Known vs. Unknown Turn-based vs. Real-time Noiseless vs. Noisy

Fully vs. Partially observable Episodic vs. Sequential Static vs. Dynamic Single vs. Multi agent Deterministic vs. Stochastic Discrete vs. Continuous Known vs. Unknown Turn-based vs. Real-time Noiseless vs. Noisy

Fully vs. Partially observable Episodic vs. Sequential Static vs. Dynamic Single vs. Multi agent Deterministic vs. Stochastic Discrete vs. Continuous Known vs. Unknown Turn-based vs. Real-time Noiseless vs. Noisy

Fully vs. Partially observable Episodic vs. Sequential Static vs. Dynamic Single vs. Multi agent Deterministic vs. Stochastic Discrete vs. Continuous Known vs. Unknown Turn-based vs. Real-time Noiseless vs. Noisy

Fully vs. Partially observable Episodic vs. Sequential Static vs. Dynamic Single vs. Multi agent Deterministic vs. Stochastic Discrete vs. Continuous Known vs. Unknown Turn-based vs. Real-time Noiseless vs. Noisy

Fully vs. Partially observable Episodic vs. Sequential Static vs. Dynamic Single vs. Multi agent Deterministic vs. Stochastic Discrete vs. Continuous Known vs. Unknown Turn-based vs. Real-time Noiseless vs. Noisy

Fully vs. Partially observable Episodic vs. Sequential Static vs. Dynamic Single vs. Multi agent Deterministic vs. Stochastic Discrete vs. Continuous Known vs. Unknown Turn-based vs. Real-time Noiseless vs. Noisy

Fully vs. Partially observable Episodic vs. Sequential Static vs. Dynamic Single vs. Multi agent Deterministic vs. Stochastic Discrete vs. Continuous Known vs. Unknown Turn-based vs. Real-time Noiseless vs. Noisy

Fully vs. Partially observable Episodic vs. Sequential Static vs. Dynamic Single vs. Multi agent Deterministic vs. Stochastic Discrete vs. Continuous Known vs. Unknown Turn-based vs. Real-time Noiseless vs. Noisy

Fully vs. Partially observable Episodic vs. Sequential Static vs. Dynamic Single vs. Multi agent Deterministic vs. Stochastic Discrete vs. Continuous Known vs. Unknown Turn-based vs. Real-time Noiseless vs. Noisy

Fully vs. Partially observable Episodic vs. Sequential Static vs. Dynamic Single vs. Multi agent Deterministic vs. Stochastic Discrete vs. Continuous Known vs. Unknown Turn-based vs. Real-time Noiseless vs. Noisy

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Presenter
Presentation Notes
Podívejme se, co to „reasoning as search“ znamená pro piškvorky. Na začátku máme prázdné pole a 9 možností kam umístit náš křížek.

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