Major: CAIRA - A Creative Artificially-Intuitive and Reasoning Agent in the Context of Ensemble Music Improvisation

这个项目的目标是工程师的创造性思维直观和推理代理CAIRA，智能计算机系统，旨在作出决策和生产的基础上推理和直觉的创造性工作？后者是在没有足够时间进行推理时作出自发决定的过程。人类和几个CAIRA代理人的网络将形成和研究，以提供学习和社会互动的动态环境中的边界条件随着时间的推移而变化，并在给定的时间间隔内作出决定的新的理解。该项目将使用即兴前卫音乐来研究智能代理的性能，但其结果将适用于其他基于时间的通信场景，这些场景需要创造性的解决方案和能够像人类一样自然通信的智能代理。CAIRA的机器听力能力将基于一个音乐识别系统，该系统模拟人类听觉外围来执行听觉场景分析（阿萨），听觉系统通过该过程提取音高，音色和节奏等特征，将声音组织成感知上有意义的单元。认知过程的模拟将包括用于推理和决策的全面认知演算，并且系统还将具有元推理，即实体反思其自身推理的能力。CAIRA的元推理能力将为人类系统地打破规则并权衡后果以实现特定目标（例如，创造性工作）的意愿提供开创性的见解。与人类直觉相关的机器将是CAIRA的另一个关键组成部分，主要目标是找出推理和元推理的不同平衡，以及直觉决策，另一方面，将导致新颖和迷人的创造力形式。更广泛的影响：基于科学家和艺术家之间独特的跨学科方法，并让工程和其他领域的学生参与项目相关课程，该项目将有助于更好地理解艺术创作过程是平衡不同创造力来源的产物（例如，基于规则的推理方法与直观决策）。CAIRA的总体架构将适用于各种音乐应用，包括自动作曲系统和基于互联网的音乐表演。CAIRA还将提供与创意机器的增强互动，使非专业人士和能力受损的用户能够参与富有表现力的音乐创作。两个例子包括CAIRA的能力，自动添加音乐纹理或伴奏到一个简单的旋律或作为一个二重奏的合作伙伴。 除此之外，该模型还将进一步理解人类思维的能力，即平衡基于自发性和对环境的即时感知的创造性决策，考虑环境和社会背景，并在创造性过程中考虑过去的培训和学习的风格规则。这种理解将适用于类似的复杂问题，如经济系统和语义网络服务，以及其他问题，创造性和及时的解决方案和/或自然的人机通信是必不可少的。

The goal of this project is to engineer the Creative Artificially-Intuitive and Reasoning Agent CAIRA, an intelligent computer system designed for making decisions and producing creative work based on both reasoning and intuition ? the latter being the process of making a spontaneous decision when there is not sufficient time for reasoning. A network of humans and several CAIRA agents will be formed and studied to provide new understanding of learning and social interaction in dynamic environments where boundary conditions change over time and decisions have to be made within a given time interval. The project will use improvised avant-garde music to study the performance of the intelligent agent, but the outcome will be applicable to other time-based communication scenarios that require creative solutions and intelligent agents that can communicate naturally, as humans do. The machine listening abilities of CAIRA will be based on a music recognition system that simulates the human auditory periphery to perform an Auditory Scene Analysis (ASA), the process by which the auditory system extracts features such as pitch, timbre, and rhythm to organize sound into perceptually meaningful units. The simulation of cognitive processes will include a comprehensive cognitive calculus for reasoning and decision-making, and the system will also possess metareasoning, that is, an entity's ability to reflect upon its own reasoning. CAIRA's capacity for metareasoning will provide groundbreaking insight into the human willingness to systematically break rules and weigh the consequences in order to achieve a given goal, for example, to produce creative work. A machine correlate to human intuition will be another key component of CAIRA, and a major goal is to find out how different balances of reasoning and metareasoning on the one hand, and intuitive decisions, on the other hand, will lead to novel and captivating forms of creativity. Broader Impact: Based on a unique interdisciplinary approach between scientists and artists, and also engaging students from engineering and other fields in project-related courses, the project will help to better understand the process of artistic creation as a product of balancing different sources of creativity (e.g., rule-based reasoning approaches vs. intuitive decision-making). The general architecture of CAIRA will be useful for various musical applications, including automated composition systems and internet-based music performances with co-located ensembles. CAIRA will also provide an enhanced interaction with creative machines that will allow non-specialists and ability-impaired users to engage in expressive musical creation. Two examples include CAIRA's ability to automatically add musical texture or an accompaniment to a simple melody or to serve as a duet partner. Beyond this, the model will further our understanding of the human mind's ability to balance creative decisions based on spontaneity and immediate perception of an environment, to factor in environmental and social context, and to consider past training and learned stylistic rules in the creative process. This understanding will be applicable to similar complex problems, such as economic systems and semantic web services, as well as other problems where creative and timely solutions and/or natural human/computer communication are essential.