Introduction to AI & AI Principles (Semester 1) WEEK 6 (07/08)

Introduction to AI &AI Principles (Semester 1)WEEK 6 (07/08) John Barnden Professor of Artificial Intelligence School of Computer Science University of Birmingham, UK

Making a Hot Drink • Your suggestions please!

Moving Around and Performing Actions(review) • Remembering a “mental map” of some sort and knowing where oneself is in such a map. Keeping track of movements. Recognizing landmarks. • Creating such a map. • Moving arms, etc. to reach objects efficiently and safely. • Grasping (etc.) objects safely.

Planning Actions: Examples • Planning is discussed in Callan ch. 9 (and 10). • Examples of planning: • Planning the sequence of steps needed to buy presents for people. • Planning how to get to a particular place. • Planning the steps needed to build something. • Planning moves in a game (whether chess, a shoot-em-up, football, …) • Planning the steps needed to convince somebody of something.

Planning Actions: Some Needs • Envisaging the effect of a series of actions. • Remembering different series of actions and their envisaged effects, so as to investigate alternatives properly. • Taking account of time constraints, effort constraints, etc. • Taking account of interactions between parts of the problem (preconditions, conflicts). • Recovering from unexpected problems and benefits when executing a plan: (partial) re-planning, • incl. because of unexpected changes in the world independent of one’s own actions. • Allowing for “known unknowns” (e.g., action effects that you know you don’t know).

Planning: Towards “Search” • Search is covered in Callan ch. 3. • In planning, one can mentally “search” through possible states of the world you could get to, or that would be useful to get to, by imagining doing actions. • (FORWARDS SEARCH) If I do this, then that would happen, and then if I do this, that would come about, or if instead I did this then that would happen, … … … … … … … • OR • (BACKWARDS SEARCH) To get such and such a (sub-)goal state, I could perhaps do this action from such and such another state, and to get to that state I could perhaps do so-and-so, or alternatively I could have done such and such … … … …

Towards Search, contd. • What order to investigate the actions that are possible from or towards any given state? Investigate all or just some? All in a bunch, or at different points in the search? • Follow a line of investigation as far as you can, and then hop back to a choice point if not getting anywhere? • Any limit on the number of states investigated, or on how far you follow any given line? • How can you measure how promising a state is? • How to take care of unexpected world conditions or changes, or unexpected effects of your own actions?

More on Search in a Later Lecture

Representation Needs in Planning • Representing the actual state of the “world”. • Keeping track of several hypothetical states and how they arise from each other. • Representing all the information needed about each possible action the system can take. This includes information about what preconditions need to hold in order for the action to apply, and what the effects of the action are (effects on world and on system itself, incl. the “cost” to the system). • Representing the goal(s) conditions or states to be achieved, sub-goal states that dynamically arise, time constraints, effort constraints, etc. • Possibly, representing relationships between actions such as conflicts. • Internally expressing general knowledge about the world (e.g., if it’s raining and I go outside my joints will rust).

Representation Needs, contd. • Possibly, remembering useful things to help further planning (a type of learning): • Useful, recurring sequences of actions (“chunking” of actions) • Abstractions from such sequences • Why (parts of) the plan succeeded • What failed and why • Why particular steps were decided upon.

Further Representation Needs(for Planning or Other Purposes) • Inferential Adequacy (has also been called Heuristic Adequacy): ability adequately to support processes for deriving new information from existing information (“inference”, “reasoning”). • Ability to include special things that, for example, speed up access, inference, learning, … • Appropriate degree of narrowness or breadth (general-purposeness) for the researcher’s aims.

Why Not Use Human Language?(further thoughts) • The need for a lot of context to remove ambiguity. Difficulty of knowing exactly what the context is. • Possibly leads to incorrectness or internal misunderstanding. • Also adds complexity and uncertainty that hurts inferential adequacy. • The syntax (grammatical structure) of human language is complex and full of historical quirks. This is a problem for all processing of the language, including inference.

Representing a State of the Worldand Expressing General Knowledge about the World(for planning or other purposes) • A state could be past, present, future, hypothetical, … • Ignore those differences for the moment.

Need to … • … represent entities (physical things, mental things, abstract things, situations, events, actions, processes, …) , properties of entities, relationships between entities, groups of entities, … • … make generalizations about types of entities • … capture propositional structureof information.

Entities: Some Examples • People, desks, faces, noses, pens, chess-pieces, windows, light-switches, rooms, buildings, towns, land areas, planets, … • Sizes, lengths, weights, times, prices, …, numbers • Written/spoken words/numbers/…, diagrams, … • Thoughts, emotions, claims, prejudices, personality types, plans, strategies, political movements, terrorism, peace, justice, … • Acts of eating, eating in general, the concept of eating, … • Similarly of saying, believing, learning, …

Properties: Some Examples • Being tall, being expensive, being stupid, having two legs, being kind, being a prime number, being a dog, being an act of violence, having a tail, being coffee, …

Relationships: Some Examples • X loving Y, X kissing Y, Y slapping X, X being married to Z, X being taller than Y, X drinking Y, X being a friend of Y, X being a square root of Y, X being less time-consuming than Y, X’s number of legs being Y, X being the end-point of Y, X’s hand grasping Y, • X being between Y and Z, X being the path from Y to Z, X’s tentacle number Z grasping Y, X giving money-amount Y to charity Z • X kissing Y at time T • X being stupid at time T, X giving money-amount Y to charity Z at time T

Entities versus Properties versus Relationships • Partly a matter of taste and convenience whether you think of something as being a property of one or more things or a relationship between things. • X being stupid at time T: timed property of X, or a relationship between X and T. • X having 2 legs: a property of X, or a relationship between X and 2. • X and Y being friends as a relationship between X and Y, or a property of X and/or a property of Y, or a property of the group consisting of X and Y • Properties and relationships are also, in principle, entities. But usually the entities are confined to those that we want to state properties of or relationships between.

Introduction to AI & AI Principles (Semester 1) WEEK 6 (07/08)