Digital control networks for virtual creatures

Robot control systems evolved with genetic algorithms traditionally take the form of floating-point neural network models. This thesis proposes that digital control systems, such as quantised neural networks and logical networks, may also be used for the task of robot control. The inspiration for this is the observation that the dynamics of discrete networks may contain cyclic attractors which generate rhythmic behaviour, and that rhythmic behaviour underlies the central pattern generators which drive lowlevel motor activity in the biological world. To investigate this a series of experiments were carried out in a simulated physically realistic 3D world. The performance of evolved controllers was evaluated on two well known control tasks—pole balancing, and locomotion of evolved morphologies. The performance of evolved digital controllers was compared to evolved floating-point neural networks. The results show that the digital implementations are competitive with floating-point designs on both of the benchmark problems. In addition, the first reported evolution from scratch of a biped walker is presented, demonstrating that when all parameters are left open to evolutionary optimisation complex behaviour can result from simple components

Undergraduate and Graduate Course Descriptions, 2022 Summer

Wright State University undergraduate and graduate course descriptions from Summer 2022

Undergraduate and Graduate Course Descriptions, 2013 Summer

Wright State University undergraduate and graduate course descriptions from Summer 2013

Undergraduate and Graduate Course Descriptions, 2013 Summer

Wright State University undergraduate and graduate course descriptions from Summer 2013

Arrows for knowledge-based circuits

Knowledge-based programs (KBPs) are a formalism for directly relating agents' knowledge and behaviour in a way that has proven useful for specifying distributed systems. Here we present a scheme for compiling KBPs to executable automata in finite environments with a proof of correctness in Isabelle/HOL. We use Arrows, a functional programming abstraction, to structure a prototype domain-specific synchronous language embedded in Haskell. By adapting our compilation scheme to use symbolic representations we can apply it to several examples of reasonable size

Undergraduate and Graduate Course Descriptions, 2016 Fall

Wright State University undergraduate and graduate course descriptions from Fall 2016

Undergraduate and Graduate Course Descriptions, 2017 Fall

Wright State University undergraduate and graduate course descriptions from Fall 2017

Undergraduate and Graduate Course Descriptions, 2017 Fall

Wright State University undergraduate and graduate course descriptions from Fall 2017