Towards the Design of Heuristics by Means of Self-Assembly

The current investigations on hyper-heuristics design have sprung up in two different flavours: heuristics that choose heuristics and heuristics that generate heuristics. In the latter, the goal is to develop a problem-domain independent strategy to automatically generate a good performing heuristic for the problem at hand. This can be done, for example, by automatically selecting and combining different low-level heuristics into a problem specific and effective strategy. Hyper-heuristics raise the level of generality on automated problem solving by attempting to select and/or generate tailored heuristics for the problem at hand. Some approaches like genetic programming have been proposed for this. In this paper, we explore an elegant nature-inspired alternative based on self-assembly construction processes, in which structures emerge out of local interactions between autonomous components. This idea arises from previous works in which computational models of self-assembly were subject to evolutionary design in order to perform the automatic construction of user-defined structures. Then, the aim of this paper is to present a novel methodology for the automated design of heuristics by means of self-assembly

An event-based architecture for solving constraint satisfaction problems

Constraint satisfaction problems (CSPs) are typically solved using conventional von Neumann computing architectures. However, these architectures do not reflect the distributed nature of many of these problems and are thus ill-suited to solving them. In this paper we present a hybrid analog/digital hardware architecture specifically designed to solve such problems. We cast CSPs as networks of stereotyped multi-stable oscillatory elements that communicate using digital pulses, or events. The oscillatory elements are implemented using analog non-stochastic circuits. The non-repeating phase relations among the oscillatory elements drive the exploration of the solution space. We show that this hardware architecture can yield state-of-the-art performance on a number of CSPs under reasonable assumptions on the implementation. We present measurements from a prototype electronic chip to demonstrate that a physical implementation of the proposed architecture is robust to practical non-idealities and to validate the theory proposed.Comment: First two authors contributed equally to this wor

Solved! Making the case for collaborative problem-solving

This report argues that the ability to solve problems with others is a crucial skill for our young people in the workplace of the future but the current education system does little to support it. Key findings Collaborative problem-solving (CPS) is an increasingly important skill to teach young people in order to prepare them for the future. Despite strong evidence for its impact, CPS is rarely taught in schools but if structured well it can reinforce knowledge and improve attainment. Significant barriers exist for teachers implementing this practice, from behaviour management to curriculum coverage, to task-design. For CPS to gain ground, a concerted shift is needed including teacher training, better resources and system level support. This report is part of Nesta’s ongoing commitment to equipping young people with the skills they need to succeed. It makes a series of recommendations on how organisations and policymakers can help support and embrace the implementation of CPS. Nesta is following this up with a series of small-scale pilots of aligned programmes in order to evaluate impact and explore how CPS can be implemented in a range of practical settings. Policy recommendations Stimulate production of quality collaborative problem-solving (CPS) resources and training, from primary education onwards. Fund existing, aligned programmes to scale and evaluate impact. Educate and involve the out-of-school learning sector and volunteer educators. Develop smarter collaborative problem-solving assessment methods. Help higher education organisations and MOOCs to track what works