Connectionist approach for global optimization

A connectionist approach for global optimization is proposed. The standard function set is tested. Results obtained, in the case of large scale problems, indicate excellent scalability of the proposed approach

Learning automata in feedforward connectionist systems

This paper analyses the behaviour of a general class of learning automata algorithms for feedforward connectionist systems in an associative reinforcement learning environment. The type of connectionist system considered is also fairly general. The associative reinforcement learning task is first posed as a constrained maximization problem. The algorithm is approximated hy an ordinary differential equation using weak convergence techniques. The equilibrium points of the ordinary differential equation are then compared with the solutions to the constrained maximization problem to show that the algorithm does behave as desired.

[Book Review] Noel Starkey (ed), Connectionist Natural Language Processing: Readings from 'Connection Science'

Review of: Noel Starkey (ed), Connectionist Natural Language Processing: Readings from 'Connection Science'

A connectionist perspective of the transition from Face-to-Face to online teaching in Higher Education

Existing research shows a slow transition to online education by many university teaching staff. A mixed methods approach is used to survey teacher educators in three jurisdictions in the UK who have made the transition to online teaching, followed by focus group and individual interviews to triangulate the data. The eight tenets of connectivism are used as a lens for analysis. Findings reveal sound pedagogical reasons for the limited choice of online tools and tutors highlight two elements, namely, self-fulfilment and their desire to continually develop as an educator, as the rationale for adopting informal professional development in the 21st century.

Connectionist approach to PID autotuning

Proportional, Integral and Derivative (PID) regulators are standard building blocks for industrial automation. The popularity of these regulatores comes from their rebust performance in a wide range of operationg conditions, and also from their functional simplicity, which makes them suitable for manual tuning.

A connectionist approach to PID autotuning

Proportional, Integral and Derivative (PID) regulators are standard building blocks for industrial automation. The popularity of these regulators comes from their rebust performance in a wide range of operating conditions, and also from their functional simplicity, which makes them suitable for manual tuning.