An Overview of Goals and
Goal Selection
Justin L. Blount
Knowledge Representation Lab
Texas Tech University
August 24, 2007
Outline
•
•
•
•
Goals
Goals in ASP agents
Goals in Situation Calculus agents
Goals in BDI agents
Goals
What question do I want to answer
• What do I do now? (goal/planning)
What do I want? (goal selection)
How do I get it? (planning)
• What is a goal?
• How to choose/select a goal?
• Goal n. the result or achievement toward which effort is
directed; aim; end. (dictionary)
Goals in ASP agents
(Baral, Gelfond, 2000)
•
Assume at each moment t the agents memory contains the
domain description and a partially ordered set G of the agents
goals.
•
A goal is a finite set of fluent literals the agents wants to
make true.
•
Partial ordering corresponds to the comparative importance
Agent loop
1. Observe world
2. Select one of the most import goal g in G to be achieved
3. Find plan a1, … an to achieve g
4
Execute a1
Goals in ASP agents
(Balduccini, 2005)
Agent loop
1. Observe world
2. Select a goal
3. Find plan a1, … an to achieve g
4
Execute a1
The selection of the current goal is performed taking into
account information such as the partial ordering of goals, the
history of the domain, the previous goal, and the action
description (e.g., to evaluate how hard/time-consuming it
will be to achieve a goal).
Goals in Situation Calculus agents
(Shapiro, Lesperance, 2001)
1.
Consistent set of goals --If the agent gets a request for g
and it already has the goal that -g , then it does not adopt
the goal that , otherwise its goal state would become
inconsistent and it would want everything.
2.
Paths to goal are finite. A maintenance goal of X is
always true is not finite, but can do X is true for next 100
time steps
Goals in Situation Calculus agents
(Shapiro, Lesperance, 2005)
Expansion
An agents goal are expanded when it is requested to do
something by another agent. Unless it currently has a
contradicting goal.
Contraction
If an agents owner REQUESTS(x) then later changes his mind.
The owner uses a CANCEL_REQUEST(x). Can only be used
if a REQUEST was executed previously
Persistence
A goal x persists over an action a, if a is not CANCEL
REQUEST, and the agent knows that if x holds then a does not
change its value.
Goals in situation calculus
(Sardina, Shapiro, 2003)
• Prioritized goals. Each goal has a priority level
• an agent that will attempt to achieve as many goals as
possible in priority order even if the agent does not know
of a plan that is guaranteed to achieve all the goals.
• Priorities are strict
• A strategy to achieve 1 High level goal is preffered to
strategy to achieve many (or all) lower level goals
Goals in Situation Calculus agents
(Shapiro,Lesperance, 2007)
1.
2.
3.
An agent should drop goal that it believes are impossible to
achieve.
However, if the agent revises its beliefs, it may later come to
believe that it was mistaken about the impossibility of
achieving the goal. In that case, the agent should readopt the
goal.
If an agent receives a request to adopt goal X, it will adopt it if
it does not conflict with a higher priority goal.
Goals in Situation Calculus agents
(Shapiro, Lesperance, 2007)
1.
2.
3.
4.
Goal should be compatible with beliefs. The situations that the agent
wants to actualize should be on a path from a situation that the agent
considers possible.
Instead of checking whether each individual goal is consistent with
beliefs, check if the set of all goals are consistent with beliefs
it could be the case that each goal is individually compatible with an
agent’s beliefs but the set of goals of the agent is incompatible, so some
of them should be dropped.
Which ones should be dropped?
1. Each agent has a preorder over goal formulae that corresponds to a
prioritization of goals
2. Chooses a maximal subset respecting this ordering
Goals in BDI agents
(D’Iverno,Kinny,Luck,Wooldridge,1998)
• Goals correspond to the tasks allocated to it
• From their agent loop
– generate new possible desires (tasks), by finding plans whose trigger event
matches an event in the event queue;
• A plan consists of subgoals or primitive actions
• Thus an agent with goal “achieve PHI” has a goal of performing
some (possibly empty) sequence of actions, such that after these
actions are performed, PHI will be true.
• Thus an agent with goal “query PHI” has a goal of performing
some (possibly empty) sequence of actions, such that after it
performs these actions, it will know whether or not PHI is true.
Thus an agent can have a goal either of achieving a state of affairs or
of determining whether the state of affairs holds.
Goals in BDI agents
(Thanagarajah, Padgham, Harland, 2002)
• Desires may be inconsistent
• Goals must be consistent
• if it is not possible to immediately form an intention towards a goal then the
goal is simply dropped.
• It certainly seems more reasonable that the agent have the ability to
‘remember’ a goal, and to form an intention regarding how to achieve it when
the environment is conducive to doing so.
• How to choose between two mutually inconsistent goals?
• if a new goal X is more important than an existing goal Y with which it
conflicts, then Y should be aborted and pursued. Otherwise, (X is less
important or same importance as Y ), X is not adopted.
– (too nieve)
• if there is no preference ordering between two goals, then we should prefer a
goal that is already adopted over one that is not:
Goals in BDI agents
(Winikoff, Padgham,Harland, 2001)
• Problem - BDI is difficult to explain and teach
• Solution - simplify
• Explicitly represent goals. (instead of desires)
– This is vital in order to enable selection between competing goals, dealing
with conflicting goals, and correctly handling goals which cannot be
pursued at the time they are created and must be delayed.
• Highlight goal selection as an important issue. By contrast, BDI systems
simply assume the existence of a selection function.
• avoidance goals, or safety constraints
(e.g. “never move the table while the robot is drilling”).
Goals in BDI agents
(Winikoff, Padgham, Harland, Thangarajah,2002)
• Goals have 2 aspects-- declarative and procedural
• Declarative -- to reason about important properties of goals
• Procedural -- to ensure goals can be achieved efficiently in dynamic
environments
• Reasoning about multiple goals (simple case 2 goals)
• Plans to achieve both may be independent
• irrational to try to achieve both X and -X simultaneously
• Necessarily consistent -- iff all possible subgoals do not conflict
• Necessarily inconsistent -- iff some necessary subgoals conflict
• Possibly inconsistent -- choose a consistent means on achieving both
• Necessarily support -- both share a common necessary subgoal
• Possibly support -- the exists a common necessary subgoal
Goals in BDI agents
(Pohkar, Braubach, lamersdorf,2005)
• Goal types -- perform, achieve, query, maintain.
• Active goals are currently pursued
• Options are inactive because the agent explicitly wants them to be
– Ex the option conflicts with a active goal
• Suspended goals must not be pursued because their context is invalid
– Will remain inactive until their context is valid and they become
options
Deliberation is executed when one of the following occurs
• Creation condition -- defines when new goal instance is created
• Context condition -- defines when a goal’s execution should be
suspended
• Drop condition -- defines when a goal instance is removed
Inhibition arc -- define a negative relationship between 2 goals
used in deliberation, constrain what goals are reconsidered
Goals in BDI agents
(Duff, Harland, Thangarajah,2006)
Maintenance goals - defines states that must remain true
rather than a state that is to be achieved.
Reactive - goals are only acted upon when the
maintenance condition is no longer true.
Proactive - anticipate failures and act in order to prevent them
from failing
( done by performing actions that we prevent the condition
from failing or suspending goals that will cause the
maintenance condition to fail)
Future -- prioritize maintenance goals via urgency
Goals in BDI agents
(Morreale,et al 2006)
A goal g1 is inconsistent with a goal g2 if and only if when
g1 succeeds, then g2 fails.
•
agent deliberates and generates g as an option
agent checks if g is possible and not inconsistent with active
goals
2. If both checks are passed then g becomes and intention
3. If case of inconsistency among g and some active goals
g becomes intention only if it is prefferred to such inconsistent
goals which will be dropped
Preference relation -- not total
since several goals can be pursued in parallel, there is no need to
prefer some goal to another goal if they are not inconsistent each
other.
References
[1] Baral,C. and Gelfond, M. 2000. Reasoning agents in Dynamic Domains, Logic
Based Artificial Intelligence , Edited By J. Minker, Kluwer.
[2] Balduccini, M. 2005. Answer Set Based Design of Highly Autonomous, Rational
Agents. PhD thesis, Texas Tech University.
[4] Shapiro, S. and Lesp´erance, Y. 2001. Modeling multiagent systems with the
cognitive agents specification language — a feature interaction resolution
application. In C. Castelfranchi and Y. Lesp´erance, editors, Proc. ATAL-2000, pages
244–259. Springer-Verlag, Berlin.
[5] Sardina, S. and Shapiro, S. 2003 Rational action in agent programs with prioritized
goals.AAMAS, 417-424
[6] Shapiro, S., Lesperance, Y., and Levesque, H., 2005. Goal Change, in Proccedings of
the IJCAI-05 Conference, Edinburgh, Scotland.
[7] Shapiro, S. and Brewka, G. 2007. Dynamic Interactions between Goals and Beliefs.
IJCAI, 2625-2630
[8] d’Inverno, M. Kinny, D. Luck, M. and Wooldridge,M. 1998. A Formal Specification
of dMARS, In Intelligent Agents IV In Proceedings of the Fourth International
Workshop on Agent Theories, Architectures and Languages, Singh, Rao and
Wooldridge (eds.), Lecture Notes in Artificial Intelligence, 1365, Springer-Verlag.
References - continued
[9] Thangarajah, J., Padgham, L., and Harland, J. 2002. Representation and reasoning
for goals in BDI agents. In Proceedings of the Twenty-Fifth Australasian Computer
Science Conference (ACSC 2002), Melbourne, Australia.
[10] Winikoff, M., Padgham, L., and Harland, J. 2001. Simplifying the Development of
Intelligent Agents. In AI2001: Advances in Artificial Intelligence. 14th Australian
Joint Conference on Artificial Intelligence. LNAI 2256, pages 557-568, Adelaide.
[11] Winikoff, M., Padgham, L., Harland, J., and Thangarajah, J. 2002. Declarative and
Procedural Goals in Intelligent Agent Systems, Proceedings of the Eighth
International Conference on Principles of Knowledge Representation and Toulouse.
[12] Pokahr, A., Braubach, L., Lamersdorf, W. 2005. A Goal Deliberation Strategy for
BDI Agent Systems, Third German conference on Multi-Agent System Technologies
[13]Duff, S., Harland, J., and Thangarajah, J. 2006. On Proactivity and Maintenance
Goals, Proceedings of the Fifth International Conference on Autonomous Agents and
Multi-Agent Systems (AAMAS'06), Hakodate.
[14]Morreale, V., Bonura, S., Francaviglia, G., Centineo, F., Cossentino, M., and Gaglio,
S. 2006. Reasoning about Goals in BDI Agents: the PRACTIONIST Framework.
Proc. Of the Workshop on Objects and Agents. Catania, Italy.