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Darwin's stagger Registered: 01/05/15 Posts: 10,797 |
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Exploring the Interplay of Human Cognition and Robotic Control Systems: A Paradigmatic Perspective on Cognitive Development and Adaptation
Part 1: In the realm of understanding human cognition, I've found that the world of robotics, particularly the concept of control systems, offers an insightful analogy to explore a paradigmatic perspective on human cognition. This paradigm isn't about suggesting humans operate like robots; rather, it provides a tangible way to visualise the complexity of our cognitive processes. Control Systems in Robotics and Human Cognition: Consider the control system of a robot, designed to balance programmed instructions with real-time environmental data processing. This dynamic allows the robot to make decisions based on a mix of predefined programming and adaptive learning, depending on the context, a mechanism strikingly similar to human decision-making. In our minds, we blend innate abilities and learned experiences, processing sensory data and our own personal history to make decisions. I believe this control system concept mirrors the human decision-making process, integrating innate cognitive abilities with experiences and environmental feedback. This decision-making is not a linear path but a continual feedback loop. Actions lead to reflections, insights are gained, learning occurs, and this learning informs future actions. The robotic analogy here is quite parallel – as a robot acts, it gathers data from these actions, learns from them, and adapts its future actions accordingly. This cycle of action, reflection, learning, and adaptation encapsulates a dynamic, evolving process, akin to the development of our cognitive strategies. Rather than a fixed process, it’s a continually changing one that represents how our methods of thinking, decision-making, and problem-solving develop and adapt, both in response to our immediate environment and as a result of our accumulated experiences. This is not just a singular process but a repeating cycle that represents the continuous development and refinement of cognition, both in humans and in advanced robotic systems. Implications of the Cognitive-Robotic Paradigm: Insights into Human Decision-Making: In summarising the implications of this paradigmatic analogy, it's clear that adopting robotics as a framework offers a unique perspective on human cognition. It underscores the notion that our cognitive strategies are not static, but dynamic, evolving and adapting through a continuous interplay of genetic predispositions, environmental interactions, and social learning. This approach offers a comprehensive understanding of the fluid and integrative nature of decision-making, applicable to both humans and robotic systems. While drawing parallels with robotics is insightful, it's essential to recognise the key differences between human cognition and robotic control systems. Human cognitive processes are far more complex, deeply influenced by a range of factors like emotions, personal perspectives, and societal norms. These elements add a unique depth and richness to the human cognitive experience, distinguishing it as markedly different from the more linear functionality of robotic systems. By exploring these control systems in robotics, we gain a clearer picture of the intricate workings of our own cognitive processes. This analogy allows us to recognise both the similarities and distinct complexities of human cognition, compared to robotic systems. It underscores the idea that our cognitive strategies are not rigid constructs but are constantly developing and adapting. This perspective offers a tangible way to understand the often abstract and complex nature of human thought and decision-making, highlighting the dynamic interplay of various factors shaping our cognitive development and adaptation. It’s a reflection of how we, as individuals, continually evolve in our ability to think, learn, and make decisions throughout our lives. In essence, this paradigmatic perspective, using the analogy of robotic control systems, provides a profound means to conceptualise human cognition. It helps us deeply appreciate how our cognitive strategies develop and adapt over time, reflecting the inherently dynamic and complex nature of human thought and decision-making processes. Part 2: Having explored the overarching framework of this paradigmatic perspective, where we draw analogies between human cognition and robotic control systems, it's now clear how this approach enriches our understanding of cognitive development and adaptation. This leads us to a deeper exploration of the specific processes involved. Building on this foundation, I'd like to delve deeper into the cycle of 'action, reflection, learning, and adaptation.' This next phase of our discussion aims to draw distinct parallels between the dynamic processes in human cognition and the operational mechanisms of control systems in robotics. Perception and Interpretation (Before Action): At this initial stage, both humans and robots engage in perception and interpretation. Humans actively process environmental stimuli, influenced by past experiences and biases. This is akin to robots, where sensors gather data and the system interprets this data in relation to programmed algorithms and past interactions. This stage is crucial as it sets the context for informed decision-making. Decision-Making (Leading to Action): Following perception, both humans and robots enter the decision-making phase. Humans combine emotional responses and logical reasoning, informed by their perception of the situation. Robots, similarly, utilise control systems to analyse their 'perceptions' and decide on a course of action based on set criteria and learned information. This phase underscores the similarity in how decisions are formulated in both realms. Action: In this stage, decisions are translated into actions. Humans might act through physical movements or mental resolutions, driven by the cognitive process. In robotics, this translates to the execution of tasks as dictated by their control systems, mirroring human actions. This parallel in execution is a key point of comparison in our analogy. Reflection and Learning: Post-action, both humans and robots undergo a phase of reflection and learning. Humans assess the outcomes of their actions, gaining insights and learning from both successes and failures. Similarly, advanced robotic systems review the results of their actions and adjust their programming for future improvement, reflecting the human process of learning from experience. Adaptation: The cycle culminates in adaptation, where both humans and robots modify their strategies based on the insights gained from reflection and learning. For humans, this can lead to behavioural changes or new thought patterns. For robots, it translates to updates in programming or algorithms, indicating a similar capacity for adaptation. Deeper Insights: Unraveling the Cognitive-Robotic Analogy's Applications and Significance: This analogy, comparing human cognition with robotic control systems, serves a significant purpose: it sheds light on the adaptive nature of our cognitive processes by paralleling them with something more tangible and well-defined. It's important to emphasise that this comparison doesn't imply that humans operate mechanically like robots. Rather, it offers a conceptual tool, helping us to better grasp the intricacies of our own cognition. Through this lens, we gain a deeper appreciation of the intricate interplay between perception, decision-making, and learning in human cognition. It brings into focus how these elements collectively contribute to our understanding of cognitive processes, especially in terms of how we develop, adapt, and control our cognitive strategies. This development and adaptation occur through a mix of innate capabilities, environmental interactions, and social learning. In this context, the cycle of 'action, reflection, learning, and adaptation' emerges as a comprehensive framework, enabling a more profound understanding of decision-making processes both in humans and advanced robotic systems. Ultimately, by drawing these parallels, we can understand the adaptive and evolving nature of human cognition, as mirrored in the sophisticated systems of robotics. This analogy provides a powerful means to conceptualise the complex and often abstract realm of human cognition, underscoring the dynamic interplay of various cognitive factors. It highlights that our cognitive processes, similar to those in advanced robotic systems, are in a state of continual development and adaptation, reflecting the complex and dynamic nature of human thought and decision-making processes. Quote:
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irregular verb Registered: 04/08/04 Posts: 37,530 |
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Lots of really great thinking going on here
before I get into some picky aspects, autonomous systems really need a telemetry tieback to responsible handlers, until the young android is considered adult and "responsible" for its own actions. this includes robotics in war. Multiple linkback channels are necessary for telemetry until the autonomous android is considered adult. A handler can release the android from linkback, but if not released and if the telemetry channels are broken, all aggressive functions must be disabled in an android that is not adult. from your list: my responses are in quotes inside this excerpt of your comment Quote:
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Darwin's stagger Registered: 01/05/15 Posts: 10,797 |
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I'm not sure that I'm referring to autonomous robots, as the idea here is to use the analogy of robotic control systems to parallel human decision making. The fate of any robot isn't my focus, and I think humans already have that 'telemetry tieback to the responsible handler' as themselves.
Disabling aggressive functions in case of broken telemetry sounds like the implication of understanding personal autonomy, and how that may include something like aggression or self harm in humans. While I agree it's important to recognise the potential of what understanding human autonomy entails, I myself am only focused on the theoretical exploration here, to 'flesh out' the theory and framework underpinning the proposed paradigm. Quote: Perhaps the fine grained detail of the perception and interpretation state in robotic systems could be exemplified or remedied by fuzzy logic. I'm not sure. But I agree with the general statement too. Quote: In regard to decision making as a sequence of perceptions, I think I agree, and that the original statement did too, because the intention is to recognise how rapid, moment-to-moment perceptions accumulate and integrate over time, significantly influencing behaviour and cognition, making is not a single fork in a path but a series of cascading perceptual reflexes. I agree that decision making in my view is more in line with the non-linear, complex nature of both human cognition and advanced robotic decision-making processes. I don't think I meant to display decision making necessarily as a discrete stage, but more as the cummulative effect, or a critical point of cummulative cascading perceptual reflexes. Quote: While I generally agree with the statement, 'Action as Part of Perceptual Reflex: The idea that action is already underway during the decision-making process, rather than being a distinct stage, adds depth to the understanding of how actions are formulated. This perspective views actions as ongoing adjustments rather than definitive steps, which is more reflective of how human cognition operates in real-time scenarios.' I think there is action in a sense underway during the decision making process, but that after enough cummulative cascading perceptual reflexes, the action becomes more 'aligned', 'succint' or easy to follow through on. The more detail the better kind of idea. Quote: I agree with the view that reflection and learning are akin to ongoing storytelling, and reviewing past actions underscores the importance of continuous learning and adaptation. A process crucial for both humans and advanced robotic systems to 'evolve' and improve. Quote: I think adaptation incorporates previous history, and recent history.
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irregular verb Registered: 04/08/04 Posts: 37,530 |
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Quote: for the purpose of reporting upon the history of actions, yes, an arbitration AFTER THE FACT of critical points can be done, however, decisions are not made as such- there is no sufficient accumulation of perceptions - what happens is that the continuing cascade wends it s way through situations. Latching upon decisions in cybernetics is an extension of mechanical engineering, of gearing and latches and limiters. We do not make decisions except in a historical view, instead we navigate paths while fulfilling needs and pursuing interests. It looks like a series of choices or decisions, but instead it is an endless living perceptive reflex barrage.
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Darwin's stagger Registered: 01/05/15 Posts: 10,797 |
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That adds more layers to consider, and blurs the lines between action, reflection, learning, and adaptation, making them interconnected phases of a fluid cycle.
Paradigms are not static; they are dynamic and subject to change as new information and perspectives emerge. Embracing this dynamic nature is part of engaging deeply with any field of study, especially one as intricate as cognitive processes and decision-making. Quote: I've tried not to have any expectations in all this, and although I think I understand what I'm doing, I still have the words, 'fluid of ouroboros' in mind. Quote:
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Darwin's stagger Registered: 01/05/15 Posts: 10,797 |
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For the refined paradigm, we adopt a dual approach within a dynamic system, encompassing both real-time decision-making and retrospective analysis. This approach enriches the system with a dynamic interplay between immediate action and reflective learning. It's pivotal in creating a system that is both responsive in the moment and insightful in retrospect, continuously adapting through a blend of actions and evaluations
Real-Time Decision-Making: Decisions are made in the moment, guided by current perceptions and environmental interactions. This ensures agility and adaptability, allowing the system or individual to effectively navigate immediate situations. Retrospective Analysis: Following actions, a reflective analysis occurs, where past decisions and outcomes are revisited. This retrospective approach offers deeper insights and lessons, allowing for a nuanced understanding of past behaviours and their consequences. Arbitration After the Fact: Within this cycle, arbitration after critical points acts as a mechanism for reflective learning. It enables a deeper understanding of past actions and decisions, gleaning insights that inform future actions. This is particularly relevant in scenarios where similar situations or decisions might arise, allowing for more informed and effective responses. Adaptive Feedback: This arbitration is integrated into the paradigm’s continuous feedback loop, serving as an adaptive mechanism that adjusts internal models or strategies based on past experiences. Enhanced Decision-Making: For systems employing fuzzy logic, this retrospective arbitration refines decision-making algorithms. By analysing past decisions against desired outcomes, adjustments can be made to better handle similar future scenarios. Balancing Immediate and Reflective Responses: The paradigm emphasises real-time responsiveness while ensuring that immediate responses are complemented by reflective learning. This balance enriches the adaptability and effectiveness of the system or individual. This paradigm views cognition and decision-making as a dynamic, multifaceted process, blending immediate action with reflective learning. It offers a comprehensive framework for understanding the complexities of continuous adaptation in a dynamic environment. Emphasising the interconnectedness of real-time responsiveness and retrospective analysis, the paradigm captures the essence of circular causality and continuous interaction. This approach provides a holistic understanding of cognitive and behavioural processes, illustrating how actions and reflections are not isolated events but part of an ongoing, adaptive cycle.
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irregular verb Registered: 04/08/04 Posts: 37,530 |
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it's still too tightly oriented to decisions. there are no decisions.
https://www.theguardian.com/env
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Darwin's stagger Registered: 01/05/15 Posts: 10,797 |
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If cognition is a dynamic, evolving process, not segmented by clear-cut decisions but characterised by constant adaptation and fluid transitions..
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Pigment of your imagination Registered: 05/26/05 Posts: 5,850 Last seen: 33 minutes, 12 seconds |
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I think there are semi-static elements that play important roles.
For humans, habit Quote: In the same way that there are no discrete chunks of time, there are no discrete objects either.... space and time are useful hallucinations Edited by Freedom (12/16/23 10:08 AM)
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Darwin's stagger Registered: 01/05/15 Posts: 10,797 |
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Change decision for a fluid transition and Arbitration After the Fact, Retrospective Analysis, Adaptive Feedback, Balancing Immediate and Reflective Responses still make sense.
What was, 'Enhanced decision-making', or analysing past decisions against desired outcomes, could just be fuzzy logic, but I'm a bit fuzzy on that atm. Fuzzy logic is just a potential extra layer, but it might already be there, given Balancing Immediate and Reflective Responses is already a part of it. Habit is encompassed within that. Maybe resulting engrams strengthen it, but I haven't explored any correlation there within this paradigm yet. Edited by sudly (12/16/23 10:23 AM)
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irregular verb Registered: 04/08/04 Posts: 37,530 |
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habit, just means reaction, which just means reflex, which in this case means perception from memory which is a cortical reflex;
and habits are cultivated perceptions: i.e. by repetition of the things that are to be learned together, in different contexts, or at different times, habits make the perceptive reflex association more accessible in more contexts.
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Registered: 11/15/09 Posts: 3,664 |
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Quote: that's very interesting redgreenvines glad i see it that way now
-------------------- with our love with our love we could save the world
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Registered: 11/15/09 Posts: 3,664 |
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it will help with action i think
-------------------- with our love with our love we could save the world
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