article

A BDI agent programming language with failure handling, declarative goals, and planning

Authors:

Sebastian Sardina,

Lin PadghamAuthors Info & Claims

Autonomous Agents and Multi-Agent Systems, Volume 23, Issue 1

Pages 18 - 70

https://doi.org/10.1007/s10458-010-9130-9

Published: 01 July 2011 Publication History

Abstract

Agents are an important technology that have the potential to take over contemporary methods for analysing, designing, and implementing complex software. The Belief-Desire-Intention (BDI) agent paradigm has proven to be one of the major approaches to intelligent agent systems, both in academia and in industry. Typical BDI agent-oriented programming languages rely on user-provided "plan libraries" to achieve goals, and online context sensitive subgoal selection and expansion. These allow for the development of systems that are extremely flexible and responsive to the environment, and as a result, well suited for complex applications with (soft) real-time reasoning and control requirements. Nonetheless, complex decision making that goes beyond, but is compatible with, run-time context-dependent plan selection is one of the most natural and important next steps within this technology. In this paper we develop a typical BDI-style agent-oriented programming language that enhances usual BDI programming style with three distinguished features: declarative goals, look-ahead planning, and failure handling. First, an account that mixes both procedural and declarative aspects of goals is necessary in order to reason about important properties of goals and to decouple plans from what these plans are meant to achieve. Second, lookahead deliberation about the effects of one choice of expansion over another is clearly desirable or even mandatory in many circumstances so as to guarantee goal achievability and to avoid undesired situations. Finally, a failure handling mechanism, suitably integrated with both declarative goals and planning, is required in order to model an adequate level of commitment to goals, as well as to be consistent with most real BDI implemented systems.

References

[1]

Alechina, N., Bordini, R. H., Hübner, J. F., Jago, M., & Logan, B. (2006). Belief revision for AgentSpeak agents. In Proc. of autonomous agents and multi-agent systems (AAMAS) (pp. 1288-1290).

[2]

Ambros-Ingerson, J., & Steel, S. (1988). Integrating planning, execution and monitoring. In Proc. of the national conference on artificial intelligence (AAAI) (pp. 83-88). St. Paul, MN.

[3]

Belecheanu, R. A., Munroe, S., Luck, M., Payne, T., Miller, T., McBurney, et al. (2006). Commercial applications of agents: Lessons, experiences and challenges. In Proc. of autonomous agents and multi-agent systems (AAMAS) (pp. 1549-1555).

[4]

Benfield, S. S., Hendrickson, J., & Galanti, D. (2006). Making a strong business case for multiagent technology. In Proc. of autonomous agents and multi-agent systems (AAMAS) (pp. 10-15).

[5]

Bordini, R. H., Hübner, J. F., & Wooldridge, M. (2007). Programming multi-agent aystems in AgentSpeak using Jason. Wiley Series in Agent Technology. Wiley, ISBN 0470029005.

[6]

Bordini, R. H., & Moreira, A. F. (2004). Proving BDI properties of agent-oriented programming languages. Annals of Mathematics and Artificial Intelligence, 42(1-3), 197-226.

Digital Library

[7]

Bratman, M. E. (1987). Intentions, plans, and practical reason. Harvard: Harvard University Press.

[8]

Broersen, J., Dastani, M., Hulstijn J., Huang Z., & der van Torre, L. (2001). The BOID architecture: Conflicts between beliefs, obligations, intentions and desires. In Proc. of the annual conference on autonomous agents (AGENTS) (pp. 9-16). Montreal, Canada: ACM Press.

[9]

Busetta, P., Rönnquist, R., Hodgson, A. & Lucas, A. (1999). JACK intelligent agents: Components for intelligent agents in Java. AgentLink Newsletter, 2, 2-5. January. Agent Oriented Software.

[10]

Clement, B. J., Durfee, E. H., & Barrett, A. C. (2007). Abstract reasoning for planning and coordination. Journal of Artificial Intelligence Research, 28, 453-515.

[11]

Cohen, P. R., & Levesque, H. J. (1990). Intention is choice with commitment. Artificial Intelligence Journal, 42, 213-261.

Digital Library

[12]

Dastani, M. (2008). 2APL: A practical agent programming language. Autonomous Agents and Multi-Agent Systems, 16(3), 214-248.

Digital Library

[13]

Dastani, M., de Boer, F. S., Dignum, F., & Meyer, J.-J. (2003). Programming agent deliberation: An approach illustrated using the 3APL language. In Proc. of autonomous agents and multi-agent systems (AAMAS) (pp. 97-104).

[14]

Dastani, M., van Riemsdijk, B., & Meyer, J. (2005). Programming multi-agent systems in 3APL. In Multi-agent programming (Chap. 2, pp. 39-67). Springer.

[15]

Dastani, M., van Riemsdijk, B., & Meyer, J.-J. (2006). Goal types in agent programming. In Proc. of autonomous agents and multi-agent systems (AAMAS) (pp. 1285-1287).

[16]

de Boer, F. S., Hindriks, K. V., van der Hoek, W., & Meyer, J.-J. (2007). A verification framework for agent programming with declarative goals. Journal of Applied Logic, 5(2), 277-302.

[17]

De Giacomo, G., Lespérance, Y., Levesque, H. J., & Sardina, S. (2009). IndiGolog: A high-level programming language for embedded reasoning agents. In R. H. Bordini, M. Dastani, J. Dix, & A. E. Fallah-Seghrouchni (Eds.), Multi-agent programming: Languages, platforms and applications (Chap.2) (pp. 31-72). NY: Springer.

[18]

de Silva, L. P. (2009). Planning in BDI agent systems. PhD thesis, School of Computer Science and Information Technology, RMIT University, Melbourne, Australia. Submitted.

[19]

de Silva, L. P., & Padgham, L. (2004). A comparison of BDI based real-time reasoning and HTN based planning. In Proc. of the Australian joint conference on AI (AI) (pp. 1167-1173).

[20]

de Silva, L. P., & Padgham, L. (2005). Planning on demand in BDI systems. In Proc. of the international conference on automated planning and scheduling (ICAPS), June. (poster).

[21]

de Silva, L. P., Sardina, S., & Padgham, L. (2009). First principles planning in BDI systems. In Proc. of autonomous agents and multi-agent systems (AAMAS) (Vol. 2, pp. 1001-1008).

[22]

Despouys, O., & Ingrand, F. F. (1999). Propice-plan: Toward a unified framework for planning and execution. In Proc. of the European conference on planning (ECP) (pp. 278-293).

[23]

d'Inverno, M., Luck, M., Georgeff, M. P., Kinny, D., & Wooldridge, M. (2004). The dMARS architechure: A specification of the distributed multi-agent reasoning system. Autonomous Agents and Multi-Agent Systems, 9(1-2), 5-53.

[24]

Dix, J., Muñoz-Avila, H., Nau, D. S., & Zhang, L. (2003). IMPACTing SHOP: Putting an AI planner into a multi-agent environment. Annals of Mathematics and Artificial Intelligence, 37(4), 381-407.

[25]

Eiter, T., Subrahmanian, T., & Pick, G. (1999). Heterogeneous active agents I: Semantics. Artificial Intelligence Journal, 108(1-2), 179-255.

Digital Library

[26]

Erol, K., Hendler, J. A., & Nau, D. S. (1996). Complexity results for HTN planning. Annals of Mathematics and Artificial Intelligence, 18(1), 69-93.

[27]

Gerevini, A., Bonet, B., & Givan, B. (Eds). (2006). Booklet of 4th international planning competition, Lake District, UK. http://www.ldc.usb.ve/~bonet/ipc5/.

[28]

Ghallab, M., Nau, D. S., & Traverso, P. (2004). Automated planning: Theory and practice. MA: Morgan Kaufmann.

[29]

Hennessy, M. (1990). The semantics of programming languages. Chichester, England: Wiley.

[30]

Hindriks, K. V., de Boer, F. S., van der Hoek, W., & Meyer, J.-J. (1999). Agent programming in 3APL. Autonomous Agents and Multi-Agent Systems, 2(4), 357-401.

Digital Library

[31]

Huber, M. J. (1999). JAM: A BDI-theoretic mobile agent architecture. In Proc. of the annual conference on autonomous agents (AGENTS) (pp. 236-243). New York, NY, USA: ACM Press.

[32]

Hübner, J. F., Bordini, R. H., & Wooldridge, M. (2006). Programming declarative goals using plan patterns. In Proc. of the international workshop on declarative agent languages and technologies (DALT) (Volume 4327 of LNCS, pp. 123-140). NY: Springer.

[33]

Ingrand, F. F., Georgeff, M. P., & Rao, A. S. (1992). An architecture for real-time reasoning and system control. IEEE Expert: Intelligent Systems and Their Applications, 7(6), 34-44.

Digital Library

[34]

Jennings, N. R. (2001). An agent-based approch for building complex software systems. Communications of the ACM, 44(4), 35-41.

Digital Library

[35]

Kambhampati, S., Mali, A. D., & Srivastava, B. (1998). Hybrid planning for partially hierarchical domains. In Proc. of the national conference on artificial intelligence (AAAI) (pp. 882-888).

[36]

Kinny, D., Georgeff, M. P. (1991). Commitment and effectiveness of situated agents. In Proc. of the international joint conference on artificial intelligence (IJCAI) (pp. 82-88).

[37]

Knoblock, C. A. (1995). Planning, executing, sensing and replaning for information gathering. In Proc. of the international joint conference on artificial intelligence (IJCAI) (pp. 1686-1693).

[38]

Knuth, D. E. (1969). The art of programming: Seminumerical algorithms (Vol.2). Reading: Addison-Wesley.

[39]

Kollingbaum, M. J., & Norman, T. J. (2003). NoA--a normative agent architecture. In Proc. of the international joint conference on artificial intelligence (IJCAI) (pp. 1465-1466).

[40]

Lin, F., & Levesque, H. J. (1998). What robots can do: Robot programs and effective achievability. Artificial Intelligence Journal, 101, 201-226.

Digital Library

[41]

Lloyd, J. W. (1987). Foundations of logic programming (2nd ed.). NY: Springer Verlag.

[42]

Long, D., & Fox, M. (2003). The 3rd international planning competition: Results and analysis. Journal of Artificial Intelligence Research, 20, 1-59.

Digital Library

[43]

Meneguzzi, F., & Luck, M. (2009). Leveraging new plans in AgentSpeak(PL). In Proc. of the international workshop on declarative agent languages and technologies (DALT) (Volume 5397 of LNCS, pp. 111-127). NY: Springer.

[44]

Moreira, A. F., Vieira, R., & Bordini, R. H. (2004). Extending the operational semantics of a BDI agent-oriented programming language for introducing speech-act based communication. In Proc. of the international workshop on declarative agent languages and technologies (DALT) (Volume 2990 of LNCS, pp. 1270-1285). NY: Springer.

[45]

Morley, D., & Myers, K. L. (2004). The SPARK agent framework. In Proc. of autonomous agents and multi-agent systems (AAMAS) (pp. 712-719).

[46]

Nau, D. S. (2007). Current trends in automated planning. AI Magazine, 28(4), 43-58.

Digital Library

[47]

Nau, D. S., Au, T.-C., Ilghami, O., Kuter, U., Wu, D., Yaman, F., Muñoz-Avila, H., & Murdock, W. (2005). Applications of SHOP and SHOP2. IEEE Intelligent Systems, 20(2), 34-41. Earlier version as Tech. Rep. CS-TR-4604, UMIACS-TR-2004-46.

Digital Library

[48]

Nau, D. S., Cao, Y., Lotem, A., & Muñoz-Avila, H. (1999). SHOP: Simple hierarchical ordered planner. In Proc. of the international joint conference on artificial intelligence (IJCAI) (pp. 968-973).

[49]

Nau, D. S., Muñoz-Avila, H., Cao, Y., Lotem, A., & Mitchell, S. (2001). Total-order planning with partially ordered subtasks. In Proc. of the international joint conference on artificial intelligence (IJCAI) (pp. 425-430).

[50]

Paolucci, M., Kalp, D., Pannu, A., Shehory, O., & Sycara, K. (1999). A planning component for RETSINA agents. In Proc. of the international workshop on agent theories, architectures, and languages (ATAL) (pp. 147-161) UK: Springer. ISBN 3-540-67200-1.

[51]

Plotkin, G. D. (1981). A structural approach to operational semantics. Technical report DAIMI-FN- 19. Denmark: Computer Science Department, Aarhus University.

[52]

Pokahr, A., Braubach, L., & Lamersdorf, W. (2003). JADEX: Implementing a BDI-infrastructure for JADE agents. EXP--in search of innovation (Special Issue on JADE), 3(3), 76-85.

[53]

Rao, A. S. (1996). Agentspeak(L): BDI agents speak out in a logical computable language. In W. Vander Velde & J. W. Perram (Eds.), Proc. of the 7th European workshop on modelling autonomous agents in a multi-agent world. (Agents breaking away) (Volume 1038 of LNCS, pp. 42-55). NY: Springer.

[54]

Rao, A. S., & Georgeff M. P. (1991). Modeling rational agents within a BDI-architecture. In Proc. of principles of knowledge representation and reasoning (KR) (pp. 473-484).

[55]

Rao, A. S., & Georgeff, M. P. (1992). An abstract architecture for rational agents. In Proc. of principles of knowledge representation and reasoning (KR) (pp. 438-449). San Mateo, CA.

[56]

Sardina, S., De Giacomo, G., Lespérance, Y., & Levesque, H. J. (2004). On the semantics of deliberation in IndiGolog--from theory to implementation. Annals of Mathematics and Artificial Intelligence, 41(2-4), 259-299.

Digital Library

[57]

Sardina, S., de Silva, L. P., & Padgham, L. (2006). Hierarchical planning in BDI agent programming languages: A formal approach. In Proc. of autonomous agents and multi-agent systems (AAMAS) (pp. 1001-1008). Hakodate, Japan.

[58]

Sardina, S., & Padgham, L. (2007). Goals in the context of BDI plan failure and planning. In Proc. of autonomous agents and multi-agent systems (AAMAS) (pp. 16-23). Hawaii, USA.

[59]

Sardina, S., & Shapiro, S. (2003). Rational action in agent programs with prioritized goals. In Proc. of autonomous agents and multi-agent systems (AAMAS) (pp. 417-424).

[60]

Shapiro, S., Lespérance, Y., & Levesquem, H. J. (2005). Goal change. In Proc. of the international joint conference on artificial intelligence (IJCAI) (pp. 582-588).

[61]

Shoham, Y. (1997). An overview of agent-oriented programming. In J. M. Bradshaw (Ed.), Software agents (pp. 271-290). Cambridge, MA: The MIT Press.

[62]

Thangarajah, J., Harland, J., Moreley, D., & Yorke-Smith, N. (2008). Suspending and resuming tasks in BDI agents. In Proc. of autonomous agents and multi-agent systems (AAMAS) (pp. 405-412).

[63]

Thangarajah, J., Morley, D., Yorke-Smith, N., & Harland, J. (2007). Aborting tasks and plans in BDI agents. In Proc. of autonomous agents and multi-agent systems (AAMAS) (pp. 8-15).

[64]

Thangarajah, J., Padgham, L., & Winikoff, M. (2003a). Detecting & avoiding interference between goals in intelligent agents. In Proc. of the international joint conference on artificial intelligence (IJCAI) (pp. 721-726).

[65]

Thangarajah, J., Padgham, L., & Winikoff, M. (2003b). Detecting & exploiting positive goal interaction in intelligent agents. In Proc. of autonomous agents and multi-agent systems (AAMAS) (pp. 401-408).

[66]

van Riemsdijk, B., Dastani, M., Dignum, F., & Meyer J.-J. (2005a). Dynamics of declarative goals in agent programming. In Proc. of the international workshop on declarative agent languages and technologies (DALT) (Volume 3476 of LNCS, (pp. 1-18). NY: Springer.

[67]

van Riemsdijk, B., Dastani, M., & Meyer, J.-J. (2005b). Semantics of declarative goals in agent programming. In Proc. of autonomous agents and multi-agent systems (AAMAS) (pp. 133-140).

[68]

van Riemsdijk, B., van der Hoek, W., & Meyer J.-J. (2003). Agent programming in dribble: From beliefs to goals with plans. In Proc. of autonomous agents and multi-agent systems (AAMAS) (pp. 393-400).

[69]

Walczak, A., Braubach, L., Pokahr, A., & Lamersdorf, W. (2006). Augmenting BDI agents with deliberative planning techniques. In Proc. of the programming multiagent systems languages, frameworks, techniques and tools workshop (PROMAS) (pp. 113-127).

[70]

Weld, D. S. (1999). Recent advances in AI planning. AI Magazine, 20 (2), 93-123.

Digital Library

[71]

Wilkins, D. E., & Myers, K. L. (1995). A common knowledge representation for plan generation and reactive execution. Journal of Logic and Computation, 5(6), 731-761.

[72]

Wilkins, D. E., Myers, K. L., Lowrance, J. D., & Wesley, L. P. (1995). Planning and reacting in uncertain and dynamic environments. Journal of Experimental and Theoretical AI, 7(1), 197-227.

[73]

Winikoff, M., Padgham, L., Harland, J., & Thangarajah, J. (2002). Declarative & procedural goals in intelligent agent systems. In Proc. of principles of knowledge representation and reasoning (KR) (pp. 470-481).

[74]

Wobcke, W. R. (2001). An operational semantics for a PRS-like agent architecture. In M. Stumptner, D. Corbett, & M. J. Brooks (Eds.), AI 2001: Advances in artificial intelligence. Berlin: Springer-Verlag.

Cited By

Porfirio DRoberts MHiatt LGrollman DBroadbent EJu WSoh HWilliams T(2024)Goal-Oriented End-User Programming of RobotsProceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction10.1145/3610977.3634974(582-591)Online publication date: 11-Mar-2024
https://dl.acm.org/doi/10.1145/3610977.3634974
Archibald BCalder MSevegnani MXu M(2024)Quantitative modelling and analysis of BDI agentsSoftware and Systems Modeling (SoSyM)10.1007/s10270-023-01121-523:2(343-367)Online publication date: 1-Apr-2024
https://dl.acm.org/doi/10.1007/s10270-023-01121-5
Stringer PCardoso RDixon CFisher MDennis LAgmon NAn BRicci AYeoh W(2023)Updating Action Descriptions and Plans for Cognitive AgentsProceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems10.5555/3545946.3598937(2370-2372)Online publication date: 30-May-2023
https://dl.acm.org/doi/10.5555/3545946.3598937
Show More Cited By

Recommendations

Hierarchical planning in BDI agent programming languages: a formal approach
AAMAS '06: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems

This paper provides a general mechanism and a solid theoretical basis for performing planning within Belief-Desire-Intention (BDI) agents. BDI agent systems have emerged as one of the most widely used approaches to implementing intelligent behaviour in ...
Aborting, suspending, and resuming goals and plans in BDI agents

Intelligent agents designed to work in complex, dynamic environments such as e-commerce must respond robustly and flexibly to environmental and circumstantial changes, including the actions of other agents. An agent must have the capability to ...
BDI Agent Reasoning with Guidance from HTN Recipes
AAMAS '17: Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems

Belief-Desire-Intention (BDI) agent systems and Hierarchical Task Network (HTN) planning systems are two popular approaches to acting and planning, both of which are based on hierarchical and context-based expansion of subgoals. Over the past three ...

Comments

Information & Contributors

Information

Published In

cover image Autonomous Agents and Multi-Agent Systems

Autonomous Agents and Multi-Agent Systems Volume 23, Issue 1

July 2011

153 pages

ISSN:1387-2532

Issue’s Table of Contents

Copyright © Copyright © 2011 The Author(s).

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 01 July 2011

Author Tags

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

45
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 28 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Porfirio DRoberts MHiatt LGrollman DBroadbent EJu WSoh HWilliams T(2024)Goal-Oriented End-User Programming of RobotsProceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction10.1145/3610977.3634974(582-591)Online publication date: 11-Mar-2024
https://dl.acm.org/doi/10.1145/3610977.3634974
Archibald BCalder MSevegnani MXu M(2024)Quantitative modelling and analysis of BDI agentsSoftware and Systems Modeling (SoSyM)10.1007/s10270-023-01121-523:2(343-367)Online publication date: 1-Apr-2024
https://dl.acm.org/doi/10.1007/s10270-023-01121-5
Stringer PCardoso RDixon CFisher MDennis LAgmon NAn BRicci AYeoh W(2023)Updating Action Descriptions and Plans for Cognitive AgentsProceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems10.5555/3545946.3598937(2370-2372)Online publication date: 30-May-2023
https://dl.acm.org/doi/10.5555/3545946.3598937
Xu MRivoalen TArchibald BSevegnani M(2023)CAN-verify: A Verification Tool For BDI AgentsiFM 202310.1007/978-3-031-47705-8_19(364-373)Online publication date: 13-Nov-2023
https://dl.acm.org/doi/10.1007/978-3-031-47705-8_19
Stringer PCardoso RDixon CFisher MDennis L(2023)Adaptive Cognitive Agents: Updating Action Descriptions and PlansMulti-Agent Systems10.1007/978-3-031-43264-4_22(345-362)Online publication date: 14-Sep-2023
https://dl.acm.org/doi/10.1007/978-3-031-43264-4_22
Archibald BCalder MSevegnani MXu M(2023)Quantitative Verification and Strategy Synthesis for BDI AgentsNASA Formal Methods10.1007/978-3-031-33170-1_15(241-259)Online publication date: 16-May-2023
https://dl.acm.org/doi/10.1007/978-3-031-33170-1_15
Winikoff MSidorenko GDignum VDignum F(2021)Why bad coffee? Explaining BDI agent behaviour with valuingsArtificial Intelligence10.1016/j.artint.2021.103554300:COnline publication date: 1-Nov-2021
https://dl.acm.org/doi/10.1016/j.artint.2021.103554
Cranefield S(2021)Enabling BDI group plans with coordination middleware: semantics and implementationAutonomous Agents and Multi-Agent Systems10.1007/s10458-021-09525-735:2Online publication date: 1-Oct-2021
https://dl.acm.org/doi/10.1007/s10458-021-09525-7
Stringer PCardoso RDixon CDennis L(2021)Implementing Durative Actions with Failure Detection in GwendolenEngineering Multi-Agent Systems10.1007/978-3-030-97457-2_19(332-351)Online publication date: 3-May-2021
https://dl.acm.org/doi/10.1007/978-3-030-97457-2_19
Archibald BCalder MSevegnani MXu M(2021)Probabilistic BDI Agents: Actions, Plans, and IntentionsSoftware Engineering and Formal Methods10.1007/978-3-030-92124-8_15(262-281)Online publication date: 6-Dec-2021
https://dl.acm.org/doi/10.1007/978-3-030-92124-8_15
Show More Cited By

View Options

View options

Media

Figures

Other

Tables

View Issue’s Table of Contents