<- main page <- Lecture 2 Lecture 3->

INTRODUCTION TO A.I.

Agents

& Perception-Action Architectures

Lecture 2

January 12, 2007

2.1	Outline of Topics
	Braitenberg Vehicles
		I
		II
		III
		Resources
	Schools of Thought in AI
		Classical AI / "good old-fashioned AI" (GOFAI)
		Behavior-based robotics
	Missing in Action
	Example Agents

2.2	Braitenberg Vehicles I

	Braitenberg Vehicle
	Ingredients
	2 sensors
	2 motors
	2 Wires


	"Love"	"Hate"

2.3	Braintenberg Vehicles II

	"Inverse love"	"Inverse hate"

2.4	Braintenberg Vehicles III

	"Curious"
	Outer light sensors	Strong positive cross-connections make vehicle steer towards light
	Inner light sensors	Weak positive same-side connections make vehicle steer away from light
	Resulting behavior	Vehicle will move towards light that is far away but when it comes closer it will not crash into it

2.5	Valentino Braitenberg Vehicles Resources
		Valentino Braitenberg: Vehicles - Experiments in Synthetic Psychology MIT Press
	Braitenberg Vehicles simulator - Downloadable Java code	http://www.mindspring.com/~gerken/vehicles/download/index.html
	Braitenberg Vehicles simulator - applet	http://www.architecture.yale.edu/872a/week4/braitenberg/
	MAVRICK - a robot architecture inspired by Braitenberg	http://faculty.washington.edu/gmobus/AdaptiveAgents/MAVRIC-EBA.html
	Java simulator (Braitenberg, Subsumption, more)	http://www.ifi.unizh.ch/~pfeifer/mitbook/braitenberg/braitenberg.html

2.6	Schools of thought in AI
	Cybernetics	Starting in the 1940s. Example works: Norbert Wiener's 1948 "Cybernetics, or Control and Communication in the Animal and Machine" and continued work such as WHAT THE FROG'S EYE TELLS THE FROG'S BRAIN by Lettvin, Maturana, McCullochs & Pitts, 1968.
	Emphasis	Effort to merge engineering/computer science and biology into a new field
	Classical AI / "good old-fashioned AI" (GOFAI)	Starting 1956: The Dartmouth Conference
	Emphasis	Logic Games Isolated models advanced competences static structures/knowledge
	Behavior-based robotics	Starting around 1985 with R. Brooks' work on subsumption architecture
	Emphasis	reactivity, speed architectural simplicity Holistic models of perception and action Robotics Simplicity
	Cognitive Science	An effort to integrate knowledge from psychology, neurophysiology, engineering, computer science, philosophy, lingustics in the study of mind. Initially pushed forward by Carnegie-Mellon. Possibly what the Cybernetics movement intended to become.

2.7	Classical AI
	"Classical AI": Top-down approach	Term used to describe "reflective" or "deliberative" approaches to AI
	Example typical topic (i.e. caricature)	Chess Argument: No animal except humans can play chess Everyone agrees that humans have "general intelligence" Thus, a machine that can play chess must have general intelligence Result: A lot of software that can play chess, yet have no general intelligence
	Contrast with "Behavior-Based AI"	"Classical AI": Sometimes it means: everything but behavior-based AI and somtimes it means: most of what was done in AI in the first three decades, and anything that follows those traditions
	Classical AI: Topics	Knowledge: Correctness, completeness Making models of the world to base decisions and plans on Representing knowledge to support simulations of high-level thinking and knowledge Specialized and general knowledge Human communication and natural language "Top-down" approach
	Classical AI: What it's good for	Inferencing Games (search, planning) Expert knowledge representation and use Symbolic/semantic representation Natural language Rule-based systems
	Missing pieces	Artificial hearing Emotion Preferences 3D object vision Artistic expression Innovation and creativity

2.8	Behavior-Based AI
	"Behavior-based AI"	Term used to describe "reactive" architectures with a tight coupling of sensors and actuators
	Example typical topic (i.e. a caricature)	Autonomous vaccum cleaner
	Contrast with "Classical AI"	"Behavior-based AI": Sometimes it means: everything that connects sensors directly to actuators and somtimes it means: most of what was done in AI in response to the failure of "classical AI" to come up with the goods
	Behavior-based AI: Topics	Complete systems Perception-action relationship Robotics Situated systems Embodied systems Behavior and architecture, as opposed to knowledge "Bottom-up" approach
	Behavior-based AI: What it's good for	Insect-like behaviors Reactive planning Instinctive behaviors Robust simple behaviors in complex, realtime environments As a robust basic component in a larger system
	Book	Ronald Arkin: Behavior-Based Robotics, MIT Press
	Java simulator (Braitenberg, Subsumption, more)	http://www.ifi.unizh.ch/~pfeifer/mitbook/braitenberg/braitenberg.html

2.9	Missing in Action
	In classical AI	Breadth; holistic architectures for agents Reactivity and handling of real-time Robustness Graceful degradation no symbolic grounding
	Behavior-based AI	Reasoning Common sense knowledge Prediction, long-term planning
	In both classical and behavior-based AI	Artificial hearing, smell Emotion Preferences 3D object vision Artistic expression Innovation and creativity
	Hybrid approaches	Combine ideas from both classical and behavior-based AI, and often other schools of thought

2.10	Example Agents
	Cog	MIT Main methodology: Subsumption architecture
	Attila / Genghis	MIT Main methodology: Competence network; subsumption architecture
	Gandalf	MIT Main methodology: Constructionist AI / CDM
	Others	AMBLER, CMU Shakey, Stanford Pengi/Sonja, Chapman & Agre ASIMO, HONDA QRIO, SONY

RODNEY BROOKS WITH COG

ATTILA - SIX-LEGGED ROBOT AT MIT

GANDALF: COMMUNICATIVE VIRTUAL HUMANOID AT MIT