Skip to content
BY-NC-ND 4.0 license Open Access Published by De Gruyter Open Access October 31, 2017

Reasoning with BDI Robots: From simulation to physical environment – Implementations and Limitations

  • Darryl N. Davis EMAIL logo and Shylaja Kanaganapalli Ramulu

Abstract

In this paper an overview of the state of research into cognitive robots is given. This is driven by insights arising from research that has moved from simulation to physical robots over the course of a number of sub-projects. A number of major issues arising from seminal research in the area are explored. In particular in the context of advances in the field of robotics and a slowly developing model of cognition and behaviour that is being mapped onto robot colonies. The work presented is ongoing but major themes such as the veracity of data and information, and their effect on robot control architectures are explored. A small number of case studies are presented where the theoretical framework has been used to implement control of physical robots. The limitations of the current research and the wider field of behavioral and cognitive robots are explored.

References

[1] H. Levesque, G. Lakemeyer, Cognitive Robotics, In F. van Harmelen, V. Lifschitz, B. Porter (Eds.), Handbook of Knowledge Representation, Elsevier, 200810.1016/S1574-6526(07)03023-4Search in Google Scholar

[2] M. Lee, U. Nehmzow, M. Rodrigues, Towards cognitive robotics: robotics, biology and developmental psychology, In D. McFarland, K. Stenning, M. McGonigle, D. Hendry (Eds.), The complex mind: an interdisciplinary approach, Basingstoke, Palgrave Macmillan, 2012, 103-126Search in Google Scholar

[3] M. Tenorth, M. Beetz, KnowRob: A knowledge processing infrastructure for cognition-enabled robots, International Journal of Robotics Research, 32(5) (2013), 566-59010.1177/0278364913481635Search in Google Scholar

[4] S. Karapinar, S. Sariel, Cognitive robots learning failure contexts through real-world experimentation, Autonomous Robots, 39(4) (2015), 469-48510.1007/s10514-015-9471-ySearch in Google Scholar

[5] Y. Wang, On Cognitive Robotics and Theories of Abstract Intelligence, 3rd International Conference on Automatic Control, Soft Computing & Human-Machine Interaction (ASME ’15), Salerno, Italy, June 27-29, 2015Search in Google Scholar

[6] Y. Wang, Abstract intelligence and cognitive robots. Journal of Behavioural Robotics, 1(1) (2010), 66-7210.2478/s13230-010-0007-zSearch in Google Scholar

[7] P. Haazebroek, S. van Dantzig, B. Hommel, A computational model of perception and action for cognitive robotics, Cognitive Processing, 12(4) (2011), 355-36510.1007/s10339-011-0408-xSearch in Google Scholar PubMed PubMed Central

[8] R. Bemelmans, G. J. Gelderblom, P. Jonker, L. de Witte, Socially Assistive Robots in Elderly Care: A Systematic Review into Effects and Effectiveness, Journal of the American Medical Directors Association, 13(2) (2012), 114-12010.1016/j.jamda.2010.10.002Search in Google Scholar PubMed

[9] Z. Kowalczuk, M. Czubenko, Intelligent decision-making system for autonomous robots, International Journal of Applied Mathematics and Computer Science, 21(4) (2011), 671-68410.2478/v10006-011-0053-7Search in Google Scholar

[10] R. Li, B. Liu, K. D. McDonald-Maier, Cognitive assisted living ambient system: a survey, Digital Communications and Networks, 1(4) (2015), 229-25210.1016/j.dcan.2015.10.003Search in Google Scholar

[11] A. Widyotriatmo, K.-S. Hong, Configuration Control of an Autonomous Vehicle under Nonholonomic and Field-of-View Constraints, International Journal of Imaging and Robotics, 15(3) (2015), 126-139Search in Google Scholar

[12] M. R. Pedersen, L. Nalpantidis, R. S. Andersen, C. Schou, S. Bøgh, V. Krüger, Ole Madsen, Robot skills for manufacturing: From concept to industrial deployment, Robotics and Computer- Integrated Manufacturing, 37 (2016), 282-29110.1016/j.rcim.2015.04.002Search in Google Scholar

[13] M. Al-Razgan, L. F. Alfallaj, N. S. Alsarhani, H. W. Alomair, Systematic Review of Robotics Use Since 2005, International ournal of Mechanical Engineering and Robotics Research, 5(2) (2016), 129-13210.18178/ijmerr.5.2.129-132Search in Google Scholar

[14] D. N. Davis, Control States and Complete Agent Architectures. Computational Intelligence, 17(4) (2001), 621-65010.1111/0824-7935.00167Search in Google Scholar

[15] D. N. Davis, J. Gwatkin, RoboCAMAL: A BDI Motivational Robot, Journal of Behavioural Robotics, 1(2) (2010), 116-12910.2478/s13230-010-0010-4Search in Google Scholar

[16] D. N. Davis, H. Miri, Probabilistic BDI in a Cognitive Robot Architecture, International Journal of Computer Science and Artificial Intelligence, 2(3) (2012), 1-1010.5963/IJCSAI0203001Search in Google Scholar

[17] A. Chella, U. Kurup, J. Laird, G. Trafton, J. Vinokurov, B. Chandrasekaran, The challenge of robotics for cognitive architectures, In Proceedings of the International Conference on Cognitive Modeling, Ottawa, ON, Canada, July 11-14, 2013, 287-290Search in Google Scholar

[18] H. Levesque, R. Reiter, High-level robotic control: Beyond planning, AAAI Spring Symposium on Integrating Robotics Research, Working notes, Palo Alto, CA, March 1998Search in Google Scholar

[19] P. Langley, J. E. Laird, S. Rogers, Cognitive architectures: Research issues and challenges, Cognitive Systems Research, 10 (2009), 141-16010.1016/j.cogsys.2006.07.004Search in Google Scholar

[20] M. L. Minsky, The Society of Mind, William Heinemann Ltd., 198710.1007/978-1-4757-1987-1_7Search in Google Scholar

[21] A. S. Boza, R. H. Guerra, A. Gajate, Artificial cognitive control system based on the shared circuits model of sociocognitive capacities. A first approach, Engineering Applications of Artificial Intelligence, 24(2) (2011), 209-21910.1016/j.engappai.2010.10.005Search in Google Scholar

[22] J. Weng, J. McClelland, A. Pentland, O. Sporns, I. Stockman, M. Sur, et al., Autonomous mental development by robots and animals, Science, 291 (2001), 599-60010.1126/science.291.5504.599Search in Google Scholar PubMed

[23] M. Asada, K. Hosoda, Y. Kuniyoshi, H. Ishiguro, T. Inui, Y. Yoshikawa, et al., Cognitive developmental robotics: a survey, IEEE Transactions on Autonomous Mental Development, 1(1) (2009), 12-3410.1109/TAMD.2009.2021702Search in Google Scholar

[24] N. Friedman, Learning Belief Networks in the Presence of Missing Values and Hidden Variables, Proceedings of the Fourteenth International Conference on Machine Learning, July 8-12, 1997, 125-133Search in Google Scholar

[25] M. M. Rahman, D. N. Davis, Machine Learning Based Missing Value Imputation Method for Clinical Datasets, Chapter 19 In G.-C. Yang, S.-L. Ao, L. Gelman (Eds.), IAENG Transactions on Engineering Technologies, ISBN 978-94-007-6190-2, Springer, 2013Search in Google Scholar

[26] P. De Bourcier, M. Wheeler, The Truth Is Out There: the Evolution of Reliability in Aggressive Communication Systems, Proceedings of the Fourth European Conference on Artificial Life, 1997, 1-10Search in Google Scholar

[27] S. Lallee, P. F. M. J. Verschure, How? Why? What? Where? When? Who? Grounding Ontology in the Actions of a Situated Social Agent, Robotics, 4 (2015), 169-193, DOI:10.3390/robotics402016910.3390/robotics4020169Search in Google Scholar

[28] P. F. M. J. Verschure, C. M. A. Pennartz, G. Pezzulo, The why, what, where, when and how of goal-directed choice: neuronal and computational principles, Philos. Trans. R. Soc. Lond B Biol. Sci., 369: 20130483 (2014), http://dx.doi.org/10.1098/rstb.2013.048310.1098/rstb.2013.0483Search in Google Scholar PubMed PubMed Central

[29] H. A. Simon, Motivational and emotional controls of cognition, Reprinted in Models of Thought, Yale University Press, 1979, 29-38 (originally Psychological Review, 74(1) (1967), 29-39)10.1037/h0024127Search in Google Scholar PubMed

[30] D. A. Norman, Twelve issues for cognitive science, Cognitive Science, 4 (1980), 1-3310.1207/s15516709cog0401_2Search in Google Scholar

[31] D. N. Davis, Cognitive Architectures for Affect and Motivation, Cognitive Computation, 2(3) (2010), 199-21610.1007/s12559-010-9053-4Search in Google Scholar

[32] R. Plutchik, The Psychology and Biology of Emotion, Harper Collins, New York, 1994Search in Google Scholar

[33] R. Plutchik, The Nature of Emotions Human emotions have deep evolutionary roots, a fact that may explain their complexity and provide tools for clinical practice, American Scientist, 89(4) (2001), 344-35010.1511/2001.4.344Search in Google Scholar

[34] P. Ekman, The Nature of Emotion: Fundamental Questions,Oxford University Press, New York, 1994Search in Google Scholar

[35] K. Scherer, Appraisal Considered as a Process of Multilevel Sequential Checking, In K. Scherer, A. Schorr, T. Johnstone (Eds.), Appraisal Processes in Emotion, Oxford University Press, New York, 2001Search in Google Scholar

[36] K. Oatley, Best Laid Schemes, Cambridge University Press, 1992Search in Google Scholar

[37] E. T. Rolls, The Brain and Emotion, Oxford University Press, 1999 Search in Google Scholar

[38] R. C. Arkin, Moving Up the Food Chain: Motivation and Emotion in Behaviour-based Robots, In J.-M. Fellous, M. A. Arbib (Eds.), Who Needs Emotions? The Brain Meets the Robot, Oxford University Press, 200510.1093/acprof:oso/9780195166194.003.0009Search in Google Scholar

[39] R. Sanz, J. Gómez, Vindication of a Rigorous Cognitive Science, Journal of Mind Theory, 0(1) (2008), 5-9Search in Google Scholar

[40] E. D. Sontag, Mathematical Control Theory: Deterministic Finite Dimensional Systems, Second Edition, Springer, New York, 1998Search in Google Scholar

[41] R.-E. Precup, H.-I. Filip, M.-B. Radac, E. M. Petriu, S. Preitl, C.-A. Dragos, Online identification of evolving Takagi-Sugeno-Kang fuzzy models for crane systems, Applied Soft Computing, 24 (2014), 1155-116310.1016/j.asoc.2014.01.013Search in Google Scholar

[42] J. Vascak, K. Hirota, Integrated decision-making system for robot soccer, Journal of Advanced Computational Intelligence and Intelligent Informatics, 15(2) (2011), 156-16310.20965/jaciii.2011.p0156Search in Google Scholar

[43] J. Vascak, M. Pal’a, Adaptation of Fuzzy Cognitive Maps for Navigation, Purposes by Migration Algorithms, International Journal of Artificial Intelligence, 8(12) (2012), 20-37Search in Google Scholar

[44] N. Hawes, A survey of motivation frameworks for intelligent systems, Artificial Intelligence, 175(5-6) (2011), 1020-103610.1016/j.artint.2011.02.002Search in Google Scholar

[45] O. Holland, A. Diamond, H. G. Marques, B. Mitra, D. Devereux, Real and apparent biological inspiration in cognitive architectures, Biologically Inspired Cognitive Architectures, 3 (2013), 105-11610.1016/j.bica.2012.07.008Search in Google Scholar

[46] GC5, UK Computing Research Committee Grand Challenge 5 (GC- 5): Architecture of Brain and Mind, University of Birmingham website, 2008, http://www.cs.bham.ac.uk/research/cogaff/gc/Search in Google Scholar

[47] D. Kahneman, A. Tversky, Prospect theory: An analysis of decision under risk, Econometrica, XLVII (1979), 263-91 10.2307/1914185Search in Google Scholar

[48] M. Quirin, J. Hertzberg, J. Kuhl, A. Stephan, Could positive affect help engineer robot control systems?, Cognitive Processing, 12(4) (2011), 375-37810.1007/s10339-011-0401-4Search in Google Scholar PubMed

[49] R. Sanz, M. G. Sánchez-Escribano, C. H. Pérez, A model of emotion as patterned metacontrol, Biologically Inspired Cognitive Architectures, 4 (2013), 79-9710.1016/j.bica.2013.02.001Search in Google Scholar

[50] A. Newell, Unified Theories of Cognition, Harvard University Press, 1990Search in Google Scholar

[51] A. Sloman, The Mind as a Control System. In C. Hookway, D. Peterson (Eds.), Philosophy and the Cognitive Sciences, Cambridge University Press, 1993, 69-11010.1017/S1358246100002460Search in Google Scholar

[52] D. N. Davis, Reactive and Motivational Agents, In J. P. Muller, M. J. Wooldridge, N. R. Jennings (Eds.), Intelligent Agents III: Agent Theories, Architectures, and Languages, Springer Verlag, 1996Search in Google Scholar

[53] D. N. Davis, S. J. Lewis, Computational Models of Emotion for Autonomy and Reasoning, Informatica, Special Edition on Perception and Emotion Based Reasoning, 27(2) (2003), 159-165Search in Google Scholar

[54] G. Bourgne, Affect-Based Multi-Agent Architecture for a 5-aside Football Simulation. M.Sc. Thesis, Department of Computer Science, University of Hull, UK, 2003, http://blacklight.hull.ac.uk/catalogue/b1858572Search in Google Scholar

[55] MobileSim, Adept Mobile Robots (2015), http://robots.mobilerobots.com/wiki/MobileSim (Last accessed July 2017)Search in Google Scholar

[56] A. S. Rao, A. P. Georgeff, BDI Agents: From Theory to Practice, Technical Note 56, Australian Artificial Intelligence Institute, April 1995, http://www.agent.ai/doc/upload/200302/rao95.pdfSearch in Google Scholar

[57] K. Bartsch, H. Wellman, Young children’s attribution of action to beliefs and desires, Child Development, 60 (1989), 946-96410.2307/1131035Search in Google Scholar

[58] S. Wahl, H. Spada, Children’s Reasoning about Intentions, Beliefs, and Behaviour, Cognitive Science Quarterly, 1 (2000), 5-34Search in Google Scholar

[59] B. J. Baars, In the Theater of Consciousness, Oxford University Press, 199710.1093/acprof:oso/9780195102659.001.1Search in Google Scholar

[60] Adept MobileRobots, http://www.mobilerobots.com/ResearchRobots.aspx, OMRON ADEPT MOBILEROBOTS LLC 2016 (Last accessed July 2017)Search in Google Scholar

[61] Parallax, ActivityBot Robot Kit, https://www.parallax.com/product/32500, Parallax Inc., 2017Search in Google Scholar

[62] V. Braitenberg, Vehicles: Experiments in synthetic psychology, Cambridge, MA: MIT Press, 1984Search in Google Scholar

[63] D. E. Berlyne, A theory of human curiosity, British Journal of Psychology, 45(3) (1954), 180-19110.1111/j.2044-8295.1954.tb01243.xSearch in Google Scholar PubMed

[64] A. Manguel, Curiosity. New Haven, CT: Yale University Press, 2015, ISBN 978-0-300-18478-5Search in Google Scholar

[65] L. Macedo, A. Cardoso, The exploration of unknown environments populated with entities by a surprise-curiositybased agent, Cognitive Systems Research, 19-20 (2012), 62-8710.1016/j.cogsys.2012.04.003Search in Google Scholar

[66] J. Schmidhuber, Developmental Robotics, Optimal Artificial Curiosity, Creativity, Music, and the Fine Arts, Connection Science, 18(2) (2006), 173-18710.1080/09540090600768658Search in Google Scholar

[67] Wiki, 2017, Wikipedia: https://en.wikipedia.org/wiki/Curiousity (Last Accessed July 2017)Search in Google Scholar

[68] M. V. Vijayakumar, D. N. Davis, K. R. Shylaja, Design of Metacontrol and Metacognition mechanisms in SMCA Using Norms and Affect rules, International Conference on Artificial Intelligence and Pattern Recognition (AIPR-09), Orlando, FL, USA, July 13-16, 2009Search in Google Scholar

[69] Pioneer 3-DX, OMRON ADEPT MOBILEROBOTS LLC 2016 http: //www.mobilerobots.com/ResearchRobots/PioneerP3DX.aspx (Last accessed 30 August 2017)Search in Google Scholar

[70] D. Forsyth, D. N. Davis, Automated Cephalometric Analysis. European Journal Of Orthodontics, 18(1) (1996), 471-47810.1093/ejo/18.1.471Search in Google Scholar

[71] C. Wei, K. V. Hindriks, An Agent-Based Cognitive Robot Architecture, In Programming Multi-Agent Systems, part of the Lecture Notes in Computer Science, 7837 (2015), 54-7110.1007/978-3-642-38700-5_4Search in Google Scholar

[72] S. Balding, D. N. Davis, Combining depth and intensity images to produce enhanced object detection for use in a robotic colony, 18th Towards Autonomous Robotic Systems (TAROS) Conference, University of Surrey, July 201710.1007/978-3-319-64107-2_10Search in Google Scholar

[73] W. Duch, R. J. Oentaryo, M. Pasquier, Cognitive Architectures: Where do we go from here? Proceedings of the 2008 conference on Artificial General Intelligence, 2008, 122-136Search in Google Scholar

[74] I. Kotseruba, O. J. A. Gonzalez, J. K. Tsotsos, A Review of 40 Years of Cognitive Architecture Research: Focus on Perception, Attention, Learning and Applications, Cornell University Library, 2016, https://arxiv.org/abs/1610.08602Search in Google Scholar

[75] M. Beetz, L. Mosenlechner, M. Tenorth, CRAM - A Cognitive Robot Abstract Machine for Everyday Manipulation in Human Environments, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, October 18-22, 2010, Taipei, Taiwan10.1109/IROS.2010.5650146Search in Google Scholar

[76] R. Sun, N. Wilson, M. Lynch, Emotion: A Unified Mechanistic Interpretation from a Cognitive Architecture, Cognitive Computation, 8(1) (2016), 1-1410.1007/s12559-015-9374-4Search in Google Scholar

[77] P. Robinson, R. El Kaliouby, Computation of emotions in man and machines, Philosophical Transactions Royal Society B, 3441 (December 2009), 3441-344710.1098/rstb.2009.0198Search in Google Scholar PubMed PubMed Central

[78] S.Wintermute, Imagery in cognitive architecture: Representation and control at multiple levels of abstraction, Cognitive Systems Research, 19-20 (2012), 1-29`10.1016/j.cogsys.2012.02.001Search in Google Scholar

Received: 2017-07-14
Accepted: 2017-09-10
Published Online: 2017-10-31
Published in Print: 2017-10-26

© 2017 Darryl N. Davis and Shylaja Kanaganapalli Ramulu

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Downloaded on 5.2.2023 from https://www.degruyter.com/document/doi/10.1515/pjbr-2017-0003/html
Scroll Up Arrow