Watson Richard
Institute for Life Sciences/Electronics and Computer Science, University of Southampton, Southampton, UK.
Biol Theory. 2024;19(1):22-36. doi: 10.1007/s13752-023-00447-z. Epub 2023 Nov 8.
In this essay we aim to present some considerations regarding a minimal but concrete notion of agency and goal-directed behavior that are useful for characterizing biological systems at different scales. These considerations are a particular perspective, bringing together concepts from dynamical systems, combinatorial problem-solving, and connectionist learning with an emphasis on the relationship between parts and wholes. This perspective affords some ways to think about agents that are concrete and quantifiable, and relevant to some important biological issues. Instead of advocating for a strict definition of minimally agential characteristics, we focus on how (even for a modest notion of agency) the agency of a system can be more than the sum of the agency of its parts. We quantify this in terms of the problem-solving competency of a system with respect to resolution of the frustrations between its parts. This requires goal-directed behavior in the sense of delayed gratification, i.e., taking dynamical trajectories that forego short-term gains (or sustain short-term stress or frustration) in favor of long-term gains. In order for this competency to belong to the system (rather than to its parts or given by its construction or design), it can involve distributed systemic knowledge that is acquired through experience, i.e., changes in the organization of the relationships among its parts (without presupposing a system-level reward function for such changes). This conception of agency helps us think about the ways in which cells, organisms, and perhaps other biological scales, can be agential (i.e., more agential than their parts) in a quantifiable sense, without denying that the behavior of the whole depends on the behaviors of the parts in their current organization.
在本文中，我们旨在提出一些关于能动性和目标导向行为的最低限度但具体的概念的思考，这些概念有助于刻画不同尺度的生物系统。这些思考是一种特定的视角，将来自动力系统、组合问题解决和联结主义学习的概念结合在一起，重点关注部分与整体之间的关系。这种视角提供了一些思考主体的方式，这些方式是具体且可量化的，并且与一些重要的生物学问题相关。我们并非主张对最低限度的能动特征进行严格定义，而是关注一个系统的能动性（即使是对于适度的能动性概念）如何能够超越其各部分能动性的总和。我们从系统解决其各部分之间冲突的问题解决能力的角度对此进行量化。这需要在延迟满足意义上的目标导向行为，即采取放弃短期收益（或承受短期压力或挫折）以换取长期收益的动态轨迹。为了使这种能力属于系统（而非其各部分，也不是由其构造或设计所赋予），它可能涉及通过经验获得的分布式系统知识，即其各部分之间关系组织的变化（而无需预先假定针对此类变化的系统级奖励函数）。这种能动性概念有助于我们思考细胞、生物体以及或许其他生物尺度在可量化意义上能够具有能动性（即比其各部分更具能动性）的方式，同时并不否认整体的行为取决于其各部分在当前组织中的行为。
