Human-Like Computing Machine Intelligence Workshop

最近在统计人工智能方面取得的显著进展，比如无人驾驶汽车的成功，以及阿尔法围棋最近击败了排名9段的韩国围棋选手李世石，这些都极大地提高了公众的意识，即计算机有可能在以前人类判断和技能的领域达到人类水平。然而，从人类的角度来看，统计人工智能技术仍然是熟练的僵尸，具有与表达目标或意图的能力分离的无意识技能。在许多具有商业价值和社会价值的环境中，缺乏与人类合作交流的能力限制了这些方法的长期潜力。研讨会将讨论与互动有关的问题，其中人类合作和沟通技能可以被研究和计算建模。虽然这些问题在符号人工智能中已经突出了一段时间，但我们还没有看到统计和符号人工智能方法的成功整合，从而实现了人类行为中存在的广泛现象。本次研讨会旨在通过明确在该领域需要优先考虑的关键问题，为EPSRC的类人计算优先领域的目标做出贡献。

Recent prominent advances in statistical AI, such as the success ofdriverless cars and Alpha Go's recent defeat ofthe 9-dan ranked South Korean Go player Lee Se-dol have considerablyincreased public awareness of the potential for computers to achievehuman-level competence in settings which were previously the exclusiverealm of human judgement and skill. However, in human termsstatistical AI techniques still act as skilled zombies, havingunconscious skills detached from the ability to express goals or intentions.The lack of ability to communicate in a co-operative fashion withhuman beings limits the long-term potential of these approachesin many commercially and socially valuable settings.The workshop will address issues related to interaction in which human co-operative and communicative skillscan be studied and modelled computationally. While many of these issues havebeen prominent for some time in symbolic AI, we are yetto see successful integration of statistical and symbolic AI approacheswhich achieves the broad range of phenomena present in human behaviour.This workshop aims to contribute to the objectives of the EPSRC's Human-LikeComputing priority area by crystalising the key issues which need tobe prioritised in this area.