IofT 1910 W Fall 2006 Week 5

1. IofT 1910 W Fall 2006Week 5 Plan for today: discuss questions asked in writeup talk about approaches to building intelligence talk about the lab on Thursday

2. 1. Fundamental principles used in the paper

3. 2. Control architecture • Model of intelligence • Traditional model • Brook’s model • Model used in this paper • Control architecture • Subsumption • Finite State Machine

4. Model of intelligenceTraditional model, according to Brooks • In the traditional model cognition mediates between perception and actions. • Actions affect the world • Perception gets information from the world to feed cognition

5. Brooks’ model • Cognition is in the eye of the observer. • Perception and action do all the work. • The world is its own best model. World Action Perception Cognition

6. Model in today’s paper?

7. AI = Rational Agents An agent is an entity that perceives and acts. More abstractly the agent is a function from percept histories to actions. The material on Agent architectures is from Russell&Norvig,”Artificial Intelligence: a Modern Approach”, Prentice-Hall, 2003

8. Agent types • We can design different agent types, from simple to more complex. • Agents operate in different environments (observable vs partially observable, deterministic vs stochastic, static vs dynamic, episodic vs sequential, discrete vs continuous, single agent vs multi-agent, etc). • The environment mostly determines the agent design.

9. The vacuum cleaner world The vacuum cleaner can perceive location and contents (in A, dirt). Actions it can do are: left, right, suck, no-op. How should the agent decide what to do?

10. Agent types: A simple reflex agent The agent reacts to the environment using its rules, but has no memory of its past actions.

11. Agent types: A reflex agent with state The agent reacts to the environment using its rules, and has memory of its past actions.

12. Agent types: A learning agent The agent can adapt its actions to increase performance.

13. Robot control architecture • At least two approaches: • The subsumption architecture, where behaviors are built by successive layers of modules, each of which is a Finite State Machine (FSM). A Subsumption Architecture builds a system by layering levels of control, allowing lower levels to override the higher ones and injecting higher level outputs into lower levels. • A finite state machine where states are connected by state transition links and where each state includes multiple behaviors. States allow decomposition of complex systems into small chunks. Transitions handle flow control. • Either one can be used. People use state machines more often than the subsumption architecture, because they are more flexible.

14. FSM vs. Subsumption FSM (ExploreMachine) Brooks’ Subsumption Control System walk No Obstacle Obstacle Detected turn Slide from “Robotics Seminar CSI445/660, Spring 2005 Robert Salkin & Shawn Turner, University at Albany,SUNY

15. Obstacle Avoidance Purposeful Search Random Search Detect Other Targets Obstacle Avoidance Homing Obstacle Avoidance Target Alignment Pick Up Target An example of an Agent using FSM: MinDART TAKE TARGET HOME SEARCH FOR TARGETS Target Dropped Target Found Target Grabbed GRAB TARGET

16. Lab on Thursday • Where: in EE/CS 2-140 • You need your U card to get in. • We’ll start learning URBI, a scripting language that can be used either with a memory stick or with the wireless network. • You can also continue using MEdit and learn how to add sounds and to program the LEDs.