public:t-720-atai:atai-16:lecture_notes_f-4_19.01.2016
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public:t-720-atai:atai-16:lecture_notes_f-4_19.01.2016 [2016/01/21 13:06] thorisson2 |
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| ====System Architecture==== | ====System Architecture==== | ||
| - | | What it is | The total system that has direct and independent control of the behavior of an Agent via its sensors and effectors. | | + | | What it is | In CS: the organization of the software that implements a system. \\ In AI: The total system that has direct and independent control of the behavior of an Agent via its sensors and effectors. | |
| - | | Why it's important | The system architecture | | + | | Why it's important | The system architecture determines what kind of information processing can be done, and what the system as a whole is capable of in a particular Task-Environemnt. | |
| | Key concepts | process types; process initiation; information storage; information flow. | | | Key concepts | process types; process initiation; information storage; information flow. | | ||
| + | | Relation to AI | The term "system" not only includes not only the processing components, the functions these implement, their input and output, and relationships, but also temporal aspects of the system's behavior as a whole. This is important in AI because any controller of an Agent is supposed to control it in such a way that its behavior can be classified as being "intelligent". But what are the necessary and sufficient components of that behavior set? | | ||
| + | | Intelligence is in part a systemic phenomenon | Thought experiment: Take any system we deem intelligent, e.g. a 10-year old human, and isolate any of his/her skills and features. A machine that implements any //single// one of these is unlikely to seem worthy of being called "intelligent" (viz chess programs), without further qualification (e.g. "a limited expert in a sub-field"). | | ||
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| + | ====CS Architecture Building Blocks==== | ||
| + | | Pipes & filters | Extension of functions. \\ Component: Each component has a set of inputs and a set of outputs. A component reads streams of data on its inputs and produces streams of data on its outputs, delivering a complete instance of the result in a standard order. \\ Pipes: Connectors in a system of such components transmit outputs of one filter to inputs of others. | | ||
| + | | Object-orientation | Abstract compound data types with associated operations. | | ||
| + | | Event-based invocation | Pre-defined event types trigger particular computation sequences in pre-defined ways. | | ||
| + | | Layered systems | System is deliberately separated into layers, a layer being a grouping of one or more sub-functions. | | ||
| + | | Hierarchical systems | System is deliberately organized into a hierarchy, where the position in the hierarchy represents one or more important (key system) parameters. | | ||
| + | | Blackboards | System employs a common data store, accessible by more than a single a sub-process of the system (often all). | | ||
| + | | Hybrid architectures | Take two or more of the above and mix together to suit your tastes. | | ||
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| + | ====Network Topologies==== | ||
| + | | Point-to-Point | Dedicated connection between nodes, shared only by a node at each end. | | ||
| + | | Bus | A message medium, shared by all nodes (or a subset). | | ||
| + | | Star | Central node serves as a conduit, forwarding to others; full structure of nodes forming a kind of star. | | ||
| + | | Ring | All nodes are connected to only two other nodes. | | ||
| + | | Mesh | All nodes are connected to all other nodes (fully connected graph); can be relaxed to partially-connected graph. | | ||
| + | | Tree | Node connections forms a hierarchical tree structure. | | ||
| + | | Pub-Sub | In publish-subscribe architectures one or more "post offices" receive requests to get certain information from nodes. | | ||
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| + | ====Coordination Hierarchies==== | ||
| + | | {{ public:t-720-atai:coordinationhierarchies.png?500 }} | | ||
| + | | A functional hierarchy organizes the execution of tasks according to their functions. A product hierarchy organizes production in little units, each focused on a particular product. \\ Several types of markets exist - here two idealized versions are show, without and with brokers. De-centralized markets require more intelligence to be present in the nodes, which can be aleviated by brokers. Brokers, however, present weak points in the system: If you have a system with only 2 brokers mediating between processors and consumers/buyers, failure in these 2 points will render the system useless. \\ Notice that in a basic program written in C++ every single character is such a potential point of failure, which is why bugs are so common in standard software. | | ||
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| | Constructionist AI | Methodology for building //cognitive agents// that relies primarily on Constructionist methodologies. | | | Constructionist AI | Methodology for building //cognitive agents// that relies primarily on Constructionist methodologies. | | ||
| | Key Limitation | Rests on the key assumption (on which CS - as a science - is built) that humans, or those with human-level intelligence, are the only ones that will create software systems. | | | Key Limitation | Rests on the key assumption (on which CS - as a science - is built) that humans, or those with human-level intelligence, are the only ones that will create software systems. | | ||
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| - | ====Architecture types in AI==== | ||
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| - | ====Important Concepts for AGI==== | ||
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| - | | Attention | The management of processing, memory, and sensory resources. | | ||
| - | | Meta-Cognition | The ability of a system to reason about itself. | | ||
| - | | Reasoning | The application of logical rules to knowledge. | | ||
| - | | Creativity | xx. | | ||
| - | | Imagination | xxx. | | ||
| - | | Understanding | | | ||
| - | | Explanation | | | ||
| - | | Learning | Acquisition of knowledge that enables more successful completion of tasks. | | ||
| - | | Life-long learning | Incremental acquisition of knowledge throughout a (non-trivially long) lifetime. | | ||
| - | | Transfer learning | The ability to transfer what has been learned in one task to another. | | ||
| - | | Autonomy | The ability to do tasks without interference / help from others. | | ||
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| - | ====*Attention==== | ||
| - | | What it is | Resource management, plain and simple. | | ||
| - | | Resources | Storage space, processing speed, memory size. | | ||
| - | | Resource management | The organization of behavior so as to make the agent more efficient and effective. | | ||
| - | | Often ignored | Very few cognitive systems or AI architectures address this issue specifically. Partly this is due to the fact that time is not considered important in information architectures, mainly due to computer science curricula not addressing the issue, due to the fact that this is a rather immature subject, which is in large part due to Alan Turing completely ignoring time. | | ||
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| - | ====*Meta-Cognition==== | ||
| - | | What it is | "Thinking about thinking". Intuitively it is what we do when we ponder our own behavior, understanding, interpretation, logic, etc. | | ||
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| - | ====*Reasoning==== | ||
| - | | What it is | Collective name for a set of logical operations that can be performed on data. | | ||
| - | | Why it's important | Since the main difference between humans and other animals can be said to be language and logic, logic is important if we are interested in human-level intelligence (and beyond). | | ||
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| - | ====Learning==== | ||
| - | | Learning from experience | yyy. | | ||
| - | | Learning by observation | yyy. | | ||
| - | | Learning from reasoning | yyy. | | ||
| - | | Multi-objective learning | yyy. | | ||
| - | | Transfer learning | yyy. | | ||
| - | | *System-wide ampliative learning | | | ||
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| - | ====*Life-Long Learning==== | ||
| - | | What it is | A term used to indicate a focus of learning research on how systems can change their learning over long periods of time. Duration here is not measured in milliseconds, years, or any such measure but is rather meant as an indication of the expectation on the system being engineered -- are the assumptions that the designers know up front regarding what is to be learned expected to hold over the lifetime of the system? | | ||
| - | | Why is it important | Systems without it could hardly be considered to have general intelligence. | | ||
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| - | ====*Autonomy==== | ||
| - | | What it is | A term we use to refer to the independence of agents - the more independent they are (of their designers, of outside aid, etc.) the more autonomous they are. | | ||
| - | | Why is it important | Systems without it could hardly be considered to have general intelligence. | | ||
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| - | ====Constructivist AI==== | ||
| - | | What it is | A term for labeling a methodology for AGI based on two main assumptions: (1) Constructionist approaches do not sufficiently address issues of key importance when implementing the . | | ||
| - | | Why it's needed | Present methods in AI will not suffice for addressing the full scope of the phenomenon of intelligence, as see in nature. | | ||
| - | | Basic tenet | That an AGI must be able to handle //new// Problems in //new// Task-Environments, and to do so it must be able to create //new// knowledge with //new// Goals (and sub-goals), and to do so their architecture must support automatic generation of //meaning//, and that constructionist methodologies do not support the creation of such system architectures. | | ||
| - | | Roots | Piaget . | | ||
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| - | ====Related (also important) Concepts==== | ||
| - | | Prediction | | | ||
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/var/www/ailab/WWW/wiki/data/pages/public/t-720-atai/atai-16/lecture_notes_f-4_19.01.2016.txt · Last modified: 2016/01/21 20:17 by thorisson2
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