CIHLI 2014, Orlando, FL, USA
CIHLI 2013, Singapore

Papers from the 1st IEEE Symposium on Computational Intelligence for Human-Like Intelligence (CIHLI), Singapore, APR 16-19, 2013

  1. Cognitive Agent and its Implementation in the Blender Game Engine Environment Starzyk, Janusz A.; Raif, Pawel
  2. Transitioning From Motivated to Cognitive Agent Model Graham, James; Starzyk, Janusz A.
  3. Multi-Game Playing - a Challenge for Computational Intelligence Mandziuk, Jacek; Ong, Yew Soon; Waledzik, Karol
  4. Perception and Prediction - A Connectionist Model Iyer, Laxmi R.; Ho, Seng-Beng
  5. Comprehensiveness and interpretability of linguistic data summaries: a natural language focused perspective Kacprzyk, Janusz; Zadrozny, Slawomir
  6. The Creativity Mechanisms in Embodied Agents: An Explanatory Model Wiedermann, Jiri
  7. Evaluating Actuators in a Purely Information-Theory Based Reward Model Skaba, Wojciech
  8. A Connectionist Model for 2-Dimensional Modal Logic Jiang, Min; Yu, Yang; Chao, Fei; Shi, Minghui; Zhou, Changle
  9. The CogPrime Architecture for Embodied Artificial General Intelligence Goertzel, Ben; Ke, Shujing; Lian, Ruiting; O'Neill, Jade; Sadeghi, Keyvan; Wang, Dingjie; Watkins, Oliver; Yu, Gino
  10. A Mind-World Correspondence Principle Goertzel, Ben
  11. Novel Methods for Energy-Based Cultural Modeling and Simulation: Why Eight Is Great in Chinese Culture Olsher, Daniel J.; Guan, Toh Heng
  12. COGVIEW & INTELNET: Nuanced Energy-Based Knowledge Representation And Integrated Cognitive-Conceptual Framework For Realistic Culture, Values, and Concept-Affected Systems Simulation Olsher, Daniel J.
  13. BrainGene: computational creativity algorithm that invents novel interesting names Pilichowski, Maciej; Duch, Wlodzislaw
  14. Characteristics and Heuristics of Human Intelligence Powers, David M. W.
  15. Sentic Blending: Scalable Multimodal Fusion for the Continuous Interpretation of Semantics and Sentics Cambria, Erik; Howard, Newton; Hsu, Jane;
    Hussain, Amir
  16. Internal Control of Human Cognition - Guidance from Theory to Model the MindBurton, Peter G.
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©Michał Okulewicz