2APL A Practical Agent Programming Language

1. 2APL A Practical Agent Programming Language March 6, 2007 Cathy Yen

2. Introduction • 3APL (triple-a-p-l) • An Abstract Agent Programming Language • 3APL project was carried out by the Intelligent Systems Group at Utrecht University, the Netherlands • it is used for implementing cognitive agents and multi-agent systems. • It provides programming constructs to implement agents in terms of beliefs, goals, plans, actions, and practical reasoning rules. • 3apl program is executed by an interpreter in Java • it makes use of an embedded Prolog reasoning engine. • Intended to bridge the gap between agent theory and agent programming

3. 3APL Architecture

4. 3APL Modules • belief base • implemented by a subset of first-order predicate language (prolog like facts and rules) • goal base • Implemented by expressions of an imperative language ( procedural or to-do goals) • plan base • built from basic actions composed through program operators sequential “;”, iteration “while-do”, conditional “if-then-else” • action base (capabilities) • Implemented as triplets consisting of action name together with pre-condition (under which action can be performed) and post-conditions (effect of the action after it’s performed). • goal plan rules • Revision blocked actions, not achievable goals, generation/optimize goals • plan revision rules – used to revise, adopt, and drop plans • Interpreter - implementing the Deliberation process • Applying reasoning rules, selecting goals and actions

5. Introducing 2APL • 2APL (double-a-p-l) • A Practical Agent Programming Language • 2APL is designed and developed at the Intelligent Systems Group at the University of Utrecht. • 2APL is the successor of 3APL • 2APL interpreter is built on the JADE platform. • It provides practical extensions with constructs that makes it easier to program in and debug • Testing, different execution modes, event and exception handling mechanism • Supports the integration of declarative concepts (belief, goals) with imperative style programming (events, plans) • Aims at improving the practical application of BDI agent programming language.

6. The 2APL Language • Specification in EBNF notation • <atom> denotes a Prolog like atomic formula starting with lowercase letter • <Atom> • <ident> denotes a string • <Var> denotes a string starting with capital letter • <ground_atom> denotes a grounded atomic formula • <testbelief> with “?” is a syntactic entity of the 2APL language

7. 2APL Language Specification

8. 2APL Language Specification

9. The 2APL Language • Composed of various ingredients • Specify different aspects of the agency • Programmed with initial state of ingredients • Some ingredient change during the execution • Beliefs and goals • Basic actions • Plans • Reasoning rules • The deliberation cycle

10. Beliefs and goals • The implementation of the initial belief base starts with the keyword ’Beliefs:’ followed by one or more belief expressions of the form <belief>. • the agent believes that there is a bomb at location (3; 4), and that the blockworld environment is clean if there are no bombs anymore and the agent is not carrying a bomb.

11. Beliefs and goals • The goals of a 2APL agent are implemented by its goal base, which consists of formulas each of which denotes a situation the agent wants to realize. The implementation of the initial goal base starts with the keyword ’Goals:’ followed by a list of goal expressions of the form <goal>. • This goal base indicates that the agent wants to achieve a desirable situation in which the blockworld is clean.

12. Basic actions • In order to achieve its goals, a 2APL agent needs to act. Basic actions specify the capabilities that an agent can perform to achieve its desirable situation. • There are six types of basic actions are distinguished: • Belief Update Action : actions to update the belief base • Communication actions • External actions • Abstract actions • Belief and Goal Test Actions : actions to test the belief and goal bases • Goal Dynamics Actions : actions to manage the dynamics of goals.

13. Basic actions – Belief Update Action • A belief update action updates the belief base of an agent when executed. • An agent can execute a belief update action if the pre-condition of the action is derivable from its belief base. • belief update actions starts with the keyword ’Beliefupdates: • an agent can remove a bomb if it is the same location as the bomb • the PickUp() indicates that this belief update action can be performed if the agent does not already carry a bomb and that after performing this action the agent will carry a bomb.

14. Basic actions – Communication Action • A communication action passes a message to another agent • One version of the communication action is the expression : Send(Receiver, Performative, Content). • Receiver referring to the receiving agent, Performative is a speech act name (e.g. inform, request, etc.), and Content is an expression representing the content of the message. • An example of a communication action is sally informing harry about a bomb location

15. Basic actions – External Action • An external action is supposed to change the external environment in which the agents operate. • The effects of external actions are assumed to be determined by the environment and might not be known to the agents • The external environment determines the effect of the action • an expression of the form Java(Env,ActionName,Return,Time-out) • The parameter Env is the name of the agent’s environment to which it has access, implemented as a Java class. • The parameter ActionName is a method call (of the Java class) that specifies the effect of the external action in the environment. • Java(blockworld, east(),_,2). • This action causes an agent to go one step to the east in the blockworld environment.

16. Basic actions – Belief and Goal Test Action • A belief test action is to test whether a belief expression is derivable from an agent’s belief base • it tests whether the agent has a certain belief. • A goal test action is to test whether a formula is derivable from the goal base • whether the agent has a certain goal from which the formula is derivable • For example, if an agent has a goal p(a) and q(b), then the goal test action p(X)! succeeds resulting in the substitution [X/a].

17. Basic actions – Goal Dynamics Action • The adopt goal and drop goal actions are used to adopt and drop a goal to and from the agent’s goal base, respectively. • The adopt goal action <adoptgoal> can have two different forms: adopta(Ф) and adoptz(Ф). • the drop goal action <dropgoal> can have three different forms: dropGoal(Ф), dropSubGoal(Ф), and dropExactGoal(Ф).

18. Plans • 2APL agent adapt plans in order to achieve its goals. • Like 3APL, A plan consists of basic actions composed by process operators. • Harry enters the blockworld by performing an external action enter. • The plans of a 2APL agent are implemented by its plan base. • The implementation of the initial plan base starts with the keyword ’Plans:’ followed by a list of plans.

19. Reasoning Rules • The 2APL programming language provides constructs to implement practical reasoning rules that can be used to implement the generation of plans. • Three types of practical reasoning rules are proposed: • planning goal rules, • procedural rules, and • plan repair rules.

20. Reasoning Rules – Planning Goal Rules • A planning goal rule can specifies that an agent should generate a plan if it has certain goals and beliefs. • A planning goal rule of an agent can be applied when the goal and belief expressions are derivable from the agent’s goal and the belief bases, respectively. • A planning goal rule is of the form: • <query>? "<-" <query> “|" <plan>

21. Reasoning Rules – Planning Goal Rules • a plan to achieve the goal clean(blockWorld) can be generated if the agent believes there is a bomb at position (X,Y).

22. Reasoning Rules – Procedural Rules • Procedural rules generate plans as a response to • the reception of messages sent by other agents, • events generated by the external environment, and • the execution of abstract actions • like planning goal rules, a procedural rule has a belief condition indicating when a received event should cause the generation of a plan. a • procedural rule can be applied if the agent has received an event and the belief query of the rule is derivable from its belief base.

23. Reasoning Rules – Procedural Rules • This rule indicates that if harry receives a message from sally informing him that there is a bomb at position (X,Y) and harry does not believe there are any bombs, then harry updates his beliefs with this new fact and adds a goal to clean the blockworld again.

24. Reasoning Rules – Plan Repair Rules • A plan repair rule indicates that if the execution of an agent’s plan fails and the agent has a certain belief, then the failed plan should be replaced by another plan. • A plan repair rule hprrulei has the following form: • <planvar> "<-" <query> “|" <planvar> • A plan repair rule of an agent can applied if: • the execution of one of its plan fails, • the failed plan can be matched with the abstract plan in the head of the rule, and • the belief query expression is derivable from the agent’s belief base.

25. Reasoning Rules – Plan Repair Rules • an example of a plan repair rule of harry. This rule is used when the execution of a plan with the external action Java(blockworld,pickup(),L) fails. It fails due to there is no bomb to be picked up; it is possibly removed by another agent. The rule states that the plan should be replaced by a plan in which the agent updates its beliefs about the location of the bombs.

26. The Deliberation Cycle • Like 3APL agent, the beliefs, goals, plans and reasoning rules form the mental states of the 2APL agent. • deliberation cycle defines what the agent should do with these mental attitudes. • It states which step the agent should perform next, e.g. execute an action or apply a reasoning rule. • The deliberation cycle can be viewed as the interpreter of the agent program, as it determines which deliberation steps should be performed in which order

27. The Deliberation Cycle of a 2APL Agent

28. The 2APL Platform • A development tool that is designed to support the implementation and execution of multi-agent systems programmed in 2APL • The 2APL platform provides a graphical interface through which a user can develop and execute 2APL multi-agent • systems using several facilities, such as a syntax-colored editor, different execution modes, and several debugging/observation tools. • The platform allows communication among agents and can run on several machines connected in a network. • Agents hosted on different 2APL platforms can communicate with each other.

29. The 2APL Platform - startup

30. The 2APL Platform – with open file

31. When MAS is selected • Log tab - to read the multi-agent system logs • Files tab - to access the file in which the multi-agent system is specified • Messages tab - to observe the messages that are exchanged between the agents when they are executed.

32. When a specific agent is selected • Overview tab - to observe the selected agent’s mental state • Log tab - to observe the agent’s execution log • The Belief updates tab - to see the specification of belief update actions that the agent can perform • PG rules tab - to see the agent’s rule that specifies how and by which plans the agent can realize its goals • PC rules tab - to view the agent’s rules that specify how the received events and messages should be handled • PR rules tab - to view the agent’s rules that specify how the agent can repair its failed plans • Files tab to - access the complete source files that specify the agent. The Edit button in the Files tab the source file will be open

33. JADE tools - • The RMA (Remote Monitoring Agent) tool - can be used to control the life cycle of the agent platform and of all the registered agents. • The sniffer - can be used for tracking messages exchanged in a JADE based environment. • You can select agents to be sniffed. Every message directed to this agent(s) or coming from this • The introspector allows to monitor and control the life-cycle of a running agent and its exchanged messages, both the queue of sent and received messages. It allows also to monitor the queue of behaviors, including executing them step-by-step.

34. RMA

35. Sniffer

36. 2APL Specific tools • The Flexible Graphical Deliberation Cycle (FGDC) tool • used to visualize and program the deliberation cycle of an agent. The agent’s deliberation cycle is used to determine what the agent should do next, e.g., • execute an action, or select a plan to reach a goal. • The state tracer • used for showing the execution trace of an agent. Each state shows the beliefs, plans, goals, and log of the agent as a result of executing one deliberation step.

37. FGDC tool

38. State tracer

39. 2APL Environments • 2APL agents can interact with environments that are implemented in Java. • You can implement your own environment, or use the “blockworld” environment that is provided by the 2APL platform (this option is not yet available)

40. Block World Environment • The blockworld is an external environment in which agents can perform actions. • The blockworldconsists of a n x n world where agents can move in four directions (north, south, east and west). • The world can contain bombs, stones, and traps. Agents can pickup and drop bombs.

41. Block World Environment

42. Reference • www.cs.uu.nl/3apl/Publications • www.cs.uu.nl/2apl/downloads