An embodied biologically constrained model of foraging: from classical and operant conditioning to adaptive real-world behavior in DAC-X
An embodied biologically constrained model of foraging: from classical and operant conditioning to adaptive real-world behavior in DAC-X
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DOI：
10.1016/j.neunet.2015.10.004
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发表时间：
2015-12-01
期刊：
影响因子：
7.8
通讯作者：
Verschure, Paul F. M. J.
中科院分区：
文献类型：
--
作者：
Maffei, Giovanni;Santos-Pata, Diogo;Verschure, Paul F. M. J.
动物通过学习、模拟和适应环境，成功地在新环境中觅食。这种目标导向行为背后的功能可以分解为5个顶级目标：“如何”、“为什么”、“什么”、“在哪里”、“何时”（H4W）。经典条件反射范式和操作性条件反射范式描述了觅食行为的一些方面。然而，尚不清楚它们的潜在神经原理的组织如何解释这些复杂的行为。我们从心智和大脑的分布式自适应控制理论（DAC）的角度来解决这个问题，该理论将这两种范式解释为表达分层体系结构的核心功能子系统的属性。特别是，我们提出了DAC- x，这是一种新的认知架构，将DAC的理论原理与哺乳动物大脑几个区域的生物学约束计算模型相结合。从探索到目标导向的思考，DAC-X通过任务依赖信息的渐进式获取、保留和表达以及相关的行动形成来支持复杂的觅食策略。我们使用基于机器人的囤积任务对DAC-X进行基准测试，包括动物觅食的主要感知和认知方面。研究表明，高效的目标导向行为是运动适应、空间编码和决策的并行学习机制相互作用的结果。综上所述，我们的研究结果表明，在经典条件反射和操作性条件反射研究的基础上，DAC-X可以解决H4W问题。最后，我们讨论了所提出的生物约束和具体化方法在研究认知以及DAC-X与其他认知架构的关系方面的优势和局限性。(C) 2015 Elsevier Ltd.版权所有。
Animals successfully forage within new environments by learning, simulating and adapting to their surroundings. The functions behind such goal-oriented behavior can be decomposed into 5 top-level objectives: 'how', 'why', 'what', 'where', 'when' (H4W). The paradigms of classical and operant conditioning describe some of the behavioral aspects found in foraging. However, it remains unclear how the organization of their underlying neural principles account for these complex behaviors. We address this problem from the perspective of the Distributed Adaptive Control theory of mind and brain (DAC) that interprets these two paradigms as expressing properties of core functional subsystems of a layered architecture. In particular, we propose DAC-X, a novel cognitive architecture that unifies the theoretical principles of DAC with biologically constrained computational models of several areas of the mammalian brain. DAC-X supports complex foraging strategies through the progressive acquisition, retention and expression of task-dependent information and associated shaping of action, from exploration to goal-oriented deliberation. We benchmark DAC-X using a robot-based hoarding task including the main perceptual and cognitive aspects of animal foraging. We show that efficient goal-oriented behavior results from the interaction of parallel learning mechanisms accounting for motor adaptation, spatial encoding and decision-making. Together, our results suggest that the H4W problem can be solved by DAC-X building on the insights from the study of classical and operant conditioning. Finally, we discuss the advantages and limitations of the proposed biologically constrained and embodied approach towards the study of cognition and the relation of DAC-X to other cognitive architectures. (C) 2015 Elsevier Ltd. All rights reserved.