Valued constraint satisfaction provides a general framework for optimisation problems over finite domains. It is a generalisation of crisp constraint satisfaction allowing the user to express preferences between solutions. Consistency is undoubtedly the most important tool for solving crisp constraints. It is not only a family of simplification operations on problem instances; it also lies at t...

This article proposes a machine learning approach to overcome the knowledge acquisition bottleneck limiting the automation of cartographic generalisation. It first explains why this automation must be guided by a differentiation of two main types of knowledge involved in this process. More precisely, it shows that cartographic generalisation is best viewed as a combination of two processes: rep...

This paper introduces a problem called the temporal knapsack problem, presents several algorithms for solving it, and compares their performance. The temporal knapsack problem is a generalisation of the knapsack problem and specialisation of the multidimensional (or multiconstraint) knapsack problem. It arises naturally in applications such as allocating communication bandwidth or CPUs in a mul...

This paper highlights 20 significant problems in AI research, with potential solutions via the SP Theory of Intelligence (SPTI) and its realisation Computer Model. With other evidence referenced paper, this is strong support SPTI as a promising foundation for development human-level broad AI, aka artificial general intelligence. The include: tendency deep neural networks to make major errors re...

The AI chips increasingly focus on implementing neural computing at low power and cost. intelligent sensing, automation, edge applications have been the market drivers for chips. Increasingly, generalisation, performance, robustness, scalability of chip solutions are compared with human-like intelligence abilities. Such a requirement to transit from application-specific general must consider se...

Crowdsourcing platforms such as Amazon Mechanical Turk have become popular for a wide variety of human intelligence tasks; however, quality control continues to be a significant challenge. Recently, we propose TURKONTROL, a theoretical model based on POMDPs to optimize iterative, crowdsourced workflows. However, they neither describe how to learn the model parameters, nor show its effectiveness...

Distance-based and generalisation-based methods are two families of artificial intelligence techniques that have been successfully used over a wide range of real-world problems. In the first case, general algorithms can be applied to any data representation by just changing the distance. The metric space sets the search and learning space, which is generally instance-oriented. In the second cas...

using image processing and artificial intelligence systems in agriculture and food industry is increasing daily. the purpose of this research is to study the feasibility of using image processing technique in predicting process of moisture content changes on green tea sheets during the drying using predictive artificial intelligence systems such as: artificial neural networks and adaptive neuro...