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A theory of goal-oriented communication

Published:03 May 2012Publication History
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Abstract

We put forward a general theory of goal-oriented communication, where communication is not an end in itself, but rather a means to achieving some goals of the communicating parties. Focusing on goals provides a framework for addressing the problem of potential “misunderstanding” during communication, where the misunderstanding arises from lack of initial agreement on what protocol and/or language is being used in communication. In this context, “reliable communication” means overcoming any initial misunderstanding between parties towards achieving a given goal. Despite the enormous diversity among the goals of communication, we propose a simple model that captures all goals.

In the simplest form of communication we consider, two parties, a user and a server, attempt to communicate with each other in order to achieve some goal of the user. We show that any goal of communication can be modeled mathematically by introducing a third party, which we call the referee, who hypothetically monitors the conversation between the user and the server and determines whether or not the goal has been achieved. Potential misunderstanding between the players is captured by allowing each player (the user/server) to come from a (potentially infinite) class of players such that each player is unaware which instantiation of the other it is talking to. We identify a main concept, which we call sensing, that allows goals to be achieved even under misunderstanding. Informally, sensing captures the user's ability (potentially using help from the server) to simulate the referee's assessment on whether the communication is achieving the goal. We show that when the user can sense progress, the goal of communication can be achieved despite initial misunderstanding. We also show that in certain settings sensing is necessary for overcoming such initial misunderstanding.

Our results significantly extend the scope of the investigation started by Juba and Sudan (STOC 2008) who studied the foregoing phenomenon in the case of a single specific goal. Our study shows that their main suggestion, that misunderstanding can be detected and possibly corrected by focusing on the goal, can be proved in full generality.

References

  1. Babai, L., Fortnow, L., and Lund, C. 1991. Non-deterministic exponential time has two-prover interactive protocols. Computat. Complex. 1, 1, 3--40.Google ScholarGoogle ScholarCross RefCross Ref
  2. Babai, L., Fortnow, L., Nisan, N., and Wigderson, A.. 1993. BPP has subexponential time simulations unless EXPTIME has publishable proofs. Computat. Complex. 3, 307--318. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Bellare, M. and Goldwasser, S. 1994. The complexity of decision versus search. SIAM J. Comput. 23, 1, 91--119. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Berners-Lee, T., Hendler, J., and Lassila, O. 2001. The semantic web. Scientific American, 34--43.Google ScholarGoogle Scholar
  5. Blum, M. and Kannan, S.. 1989. Designing programs that check their work. In Proceedings of the 21st Annual ACM Symp. Theory of Comput. (STOC). 86--97. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Briggs, P., Srivastava, L., and International Telecommunication Union. 2005. The Internet of Things. 7th ITU Internet report. International Telecommunication Union, Geneva.Google ScholarGoogle Scholar
  7. Dewey, J. 1929. Experience and Nature. Norton, New York.Google ScholarGoogle Scholar
  8. Goldreich, O., Juba, B., and Sudan, M. 2009. A theory of goal-oriented communication. Tech. rep. TR09-075, Electronic Colloquium on Computational Complexity (ECCC).Google ScholarGoogle Scholar
  9. Goldreich, O., Micali, S., and Wigderson, A. 1991. Proofs that yield nothing but their validity or all languages in NP have zero-knowledge proof systems. J. ACM 38, 3, 691--729. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Goldwasser, S., Micali, M., and Rackoff, C. 1989. The knowledge complexity of interactive proof systems. SIAM J. Comput. 18, 186--208. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Hutter, M. 2004. Universal Artificial Intelligence. Springer, Berlin. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Juba, B. 2011. Universal Semantic Communication. Springer, Berlin. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Juba, B., Kalai, A., Khanna, S., and Sudan, M. 2011. Compression without a common prior: An information-theoretic justification for ambiguity in language. In Proceedings of the 2nd Symposium on Innovations in Computer Science. 79--86.Google ScholarGoogle Scholar
  14. Juba, B. and Sudan, M. 2008a. Universal semantic communication I. In Proceedings of the 40th Annual ACM Symposium on Theory of Computing (STOC), 123--132. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Juba, B. and Sudan, M. 2008b. Universal semantic communication II: A theory of goal-oriented communication. Tech. rep. TR08-095, Electronic Colloquium on Computational Complexity (ECCC).Google ScholarGoogle Scholar
  16. Juba, B. and Sudan, M. 2011. Efficient semantic communication via compatible beliefs. In Proceedings of the 2nd Symposium on Innovations in Computer Science. 22--31.Google ScholarGoogle Scholar
  17. Juba, B. and Vempala, S. 2011. Semantic communication for simple goals is equivalent to on-line learning. In Proceedings of the 22nd International Conference on Algorithmic Learning Theory. Lecture Notes in Artificial Intelligence Series, vol. 6925, Springer, 277--291. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Lund, C., Fortnow, L., Karloff, H., and Nisan, N. 1992. Algebraic methods for interactive proof systems. J. ACM 39, 4, 859--868. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Malinowski, B. 1923. The problem of meaning in primitive languages. In The Meaning of Meaning, C. K. Ogden and I. A. Richards, Eds. Harcourt Brace Jovanovich, New York.Google ScholarGoogle Scholar
  20. Russell, S. and Subramanian, D. 1995. Provably bounded-optimal agents. J. Artif. Intel. Res. 2, 575--609. (Preliminary version with R. Parr in 13th IJCAI, 1993.) Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Shamir, A. 1992. IP = PSPACE. J. ACM 39, 4, 869--877. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Shannon, C. 1948. A mathematical theory of communication. Bell Syst. Tech. J. 27, 379--423, 623--656.Google ScholarGoogle ScholarCross RefCross Ref
  23. Shadbolt, N., Berners-Lee, T., and Hall, W. 2006. The semantic web revisited. IEEE Intelli. Sys. 21, 3, 96--101. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Uckelmann, D., Harrison, M., and Michahelles, F. 2011. An architectural approach towards the future internet of things. In Architecting the Internet of Things, D. Uckelmann, M. Harrison, and F. Michahelles, Eds. Springer, Berlin, 1--24.Google ScholarGoogle Scholar
  25. Uckelmann, D., Harrison, M., and Michahelles, F. 2011b. Architecting the Internet of Things. Springer, Berlin. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Wittgenstein, L. 1958. The Blue and Brown Books: Preliminary Studies for the ‘Philosophical Investigations’. Harper & Row, New York.Google ScholarGoogle Scholar
  27. Wittgenstein, L. 2001. Philosophical Investigations. Basil Blackwell, Malden.Google ScholarGoogle Scholar

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      • Published in

        cover image Journal of the ACM
        Journal of the ACM  Volume 59, Issue 2
        April 2012
        175 pages
        ISSN:0004-5411
        EISSN:1557-735X
        DOI:10.1145/2160158
        Issue’s Table of Contents

        Copyright © 2012 ACM

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        Publication History

        • Published: 3 May 2012
        • Revised: 1 January 2012
        • Accepted: 1 January 2012
        • Received: 1 February 2011
        Published in jacm Volume 59, Issue 2

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