Now showing items 38-44 of 44

  • [2014-09-19] Reconfigurable middleware architectures for large scale sensor networks 

    Brennan, Sean M.
    Wireless sensor networks, in an effort to be energy efficient, typically lack the high-level abstractions of advanced programming languages. Though strong, the dichotomy between these two paradigms can be overcome. ...
  • [2014-09-12] Reinforcement Learning and Planning for Preference Balancing Tasks 

    Faust, Aleksandra
    Robots are often highly non-linear dynamical systems with many degrees of freedom, making solving motion problems computationally challenging. One solution has been reinforcement learning (RL), which learns through ...
  • [2013-07-02] Scaling in the immune system 

    Banerjee, Soumya
    How different is the immune system in a human from that of a mouse? Do pathogens replicate at the same rate in different species? Answers to these questions have impact on human health since multi-host pathogens that jump ...
  • [2010-09-09] Security in network games 

    Navin, Rustagi
    Attacks on the Internet are characterized by several alarming trends: 1) increases in frequency; 2) increases in speed; and 3) increases in severity. Modern computer worms simply propagate too quickly for human detection. ...
  • [2015-06-26] Selfishness and Malice in Distributed Systems 

    Saad, George
    Large-scale distributed systems are increasingly prevalent. Two issues can impact the performance of such systems: selfishness and malice. Selfish players can reduce social welfare of games, and malicious nodes can disrupt ...
  • [2010-02-09] Term rewriting with built-in numbers and collection data structures 

    Falke, Stephan
    Term rewrite systems have been extensively used in order to model computer programs for the purpose of formal verification. This is in particular true if the termination behavior of computer programs is investigated, and ...
  • [2011-02-09] Three algorithms for causal learning 

    Rammohan, Roshan Ram
    The field of causal learning has grown in the past decade, establishing itself as a major focus in artificial intelligence research. Traditionally, approaches to causal learning are split into two areas. One area involves ...