Does an artificial intelligence perform market manipulation with its own discretion? -- A genetic algorithm learns in an artificial market simulation [PDF]
2020 IEEE Symposium Series on Computational Intelligence (SSCI), 2020 Who should be charged with responsibility for an artificial intelligence performing market manipulation have been discussed. In this study, I constructed an artificial intelligence using a genetic algorithm that learns in an artificial market simulation, and investigated whether the artificial intelligence discovers market manipulation through learning
arxiv +1 more source
The Artificial Scientist: Logicist, Emergentist, and Universalist Approaches to Artificial General Intelligence [PDF]
Proceedings of the 14th International Conference on Artificial
General Intelligence. 2021. Lecture Notes in Computer Science, vol 13154.
Springer. pp. 45-54, 2021 We attempt to define what is necessary to construct an Artificial Scientist, explore and evaluate several approaches to artificial general intelligence (AGI) which may facilitate this, conclude that a unified or hybrid approach is necessary and explore two theories that satisfy this requirement to some degree.
arxiv +1 more source
The Governance of Physical Artificial Intelligence [PDF]
arXiv, 2023 Physical artificial intelligence can prove to be one of the most important challenges of the artificial intelligence. The governance of physical artificial intelligence would define its responsible intelligent application in the society.
arxiv
Perspective: Purposeful Failure in Artificial Life and Artificial Intelligence [PDF]
arXiv, 2021 Complex systems fail. I argue that failures can be a blueprint characterizing living organisms and biological intelligence, a control mechanism to increase complexity in evolutionary simulations, and an alternative to classical fitness optimization.
arxiv
The case for psychometric artificial general intelligence [PDF]
arXiv, 2020 A short review of the literature on measurement and detection of artificial general intelligence is made. Proposed benchmarks and tests for artificial general intelligence are critically evaluated against multiple criteria. Based on the findings, the most promising approaches are identified and some useful directions for future work are proposed.
arxiv
Watershed of Artificial Intelligence: Human Intelligence, Machine Intelligence, and Biological Intelligence [PDF]
arXiv, 2021 This article reviews the "Once learning" mechanism that was proposed 23 years ago and the subsequent successes of "One-shot learning" in image classification and "You Only Look Once - YOLO" in objective detection. Analyzing the current development of Artificial Intelligence (AI), the proposal is that AI should be clearly divided into the following ...
arxiv
Artificial Intelligence Technology analysis using Artificial Intelligence patent through Deep Learning model and vector space model [PDF]
arXiv, 2021 Thanks to rapid development of artificial intelligence technology in recent years, the current artificial intelligence technology is contributing to many part of society. Education, environment, medical care, military, tourism, economy, politics, etc. are having a very large impact on society as a whole. For example, in the field of education, there is
arxiv
Artificial Creations: Ascription, Ownership, Time-Specific Monopolies [PDF]
arXiv, 2020 Creativity has always been synonymous with humans. No other living species could boast of creativity as humans could. Even the smartest computers thrived only on the ingenious imaginations of its coders. However, that is steadily changing with highly advanced artificially intelligent systems that demonstrate incredible capabilities to autonomously (i.e.
arxiv
Taking the redpill: Artificial Evolution in native x86 systems [PDF]
arXiv, 2011 In analogon to successful artificial evolution simulations as Tierra or avida, this text presents a way to perform artificial evolution in a native x86 system. The implementation of the artificial chemistry and first results of statistical experiments are presented.
arxiv
Examining correlation between trust and transparency with explainable artificial intelligence [PDF]
arXiv, 2021 Trust between humans and artificial intelligence(AI) is an issue which has implications in many fields of human computer interaction. The current issue with artificial intelligence is a lack of transparency into its decision making, and literature shows that increasing transparency increases trust. Explainable artificial intelligence has the ability to
arxiv