Multi-Agent Word Guessing Game

  • Gabino Luis
    University of Salamanca u147689[at]
  • David Suárez
    University of Salamanca
  • Alfonso J. Mateos
    University of Salamanca


The task of creating algorithms to solve a problem is surely a hard thing as it can be the fact of evaluating them. A well designed algorithm can be very powerful but, it may lack of efficiency at some aspects. This paper proposes a multi-agent system based game with three types of agents: CBot, ABot and QBot, which stands for Coordinator, Answer and Question. They will play a game based on questions and answers, where each of the QBots uses a different algorithm to guess a word. The CBot has the responsibility of the efficiency measurements, receiving and manipulating the ABot reports. The game will finish once all QBots give the correct answer and after that, the efficiency of the algorithms thanks to the CBot. Using this method, it is easier to determine which algorithm is the best with a given performance measurement.
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Agarwal, A., Gurumurthy, S., Sharma, V., and Sycara, K., 2018. Mind Your Language: Learning Visually Grounded Dialog in a Multi-Agent Setting. arXiv preprint arXiv:1808.04359.

Antol, S., Agrawal, A., Lu, J., Mitchell, M., Batra, D., Lawrence Zitnick, C., and Parikh, D., 2015. Vqa: Visual question answering. In Proceedings of the IEEE international conference on computer vision, pages 2425-2433. -

Das, A., Kottur, S., Gupta, K., Singh, A., Yadav, D., Moura, J., Parikh, D., and Batra, D., 2016. Visual dialog. -

CoRR abs/1611.08669.

García, O., Chamoso, P., Prieto, J., Rodríguez, S., and de la Prieta, F., 2017. A serious game to reduce consumption in smart buildings. In International Conference on Practical Applications of Agents and Multi-Agent Systems, pages 481-493. Springer. -

Goyal, Y., Khot, T., Summers-Stay, D., Batra, D., and Parikh, D., 2017. Making the V in VQA matter: Elevating the role of image understanding in Visual Question Answering. In CVPR, page 3. -

Johnson, J., Karpathy, A., and Fei-Fei, L., 2016. Densecap: Fully convolutional localization networks for dense captioning. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 4565-4574. -

Kiros, R., Salakhutdinov, R., and Zemel, R., 2014. Multimodal neural language models. In International Conference on Machine Learning.

Lu, J., Xiong, C., Parikh, D., and Socher, R., 2017. Knowing when to look: Adaptive attention via a visual sentinel for image captioning. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), volume 6, page 2. -

De la Prieta, F., Di Mascio, T., Marenzi, I., and Vittorini, P., 2013. Pedagogy-Driven Smart Games for Primary School Children. In 2nd International Workshop on Evidence-based Technology Enhanced Learning, pages 33-41. Springer. -

Russell, S. J. and Norvig, P., 2016. Artificial intelligence: a modern approach. Malaysia; Pearson Education Limited,.

Vinyals, O., Toshev, A., Bengio, S., and Erhan, D., 2015. Show and tell: A neural image caption generator. In -

Proceedings of the IEEE conference on computer vision and pattern recognition, pages 3156-3164.

Xu, K., Ba, J., Kiros, R., Cho, K., Courville, A., Salakhudinov, R., Zemel, R., and Bengio, Y., 2015. Show, attend and tell: Neural image caption generation with visual attention. In International conference on machine learning, pages 2048-2057.

Yao, T., Pan, Y., Li, Y., Qiu, Z., and Mei, T., 2017. Boosting image captioning with attributes. In IEEE International Conference on Computer Vision, ICCV, pages 22-29. -

Zhang, P., Goyal, Y., Summers-Stay, D., Batra, D., and Parikh, D., 2016. Yin and yang: Balancing and answering binary visual questions. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 5014-5022. -
Luis, G., Suárez, D., & Mateos, A. J. (2018). Multi-Agent Word Guessing Game. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 7(4), 17–26.


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