It has been one of the great challenges of neuro-symbolic integration to represent recursive logic programs using neural networks of finite size. In this paper, we propose to imple...
Ekaterina Komendantskaya, Krysia Broda, Artur S. d...
The paper proposes a methodology to assist the designer at the initial stages of the design synthesis process by enabling him/her to employ knowledge and algorithms existing in gr...
This paper presents a conceptual framework for understanding knowledge integration in distributed networks of practice. The framework builds upon Grant’s knowledge-based theory ...
One potential strength of recurrent neural networks (RNNs) is their – theoretical – ability to find a connection between cause and consequence in time series in an constraint-...
Abstract. We present a new technique for analyzing the rate of convergence of local dynamics in bargaining networks. The technique reduces balancing in a bargaining network to opti...