What Is a Knowledge Representation? - Leitura de artigo

SPRING 1993 17

What Is a Knowledge Representation?

Randall Davis, Howard Shrobe, and Peter Szolovits

... In this article, we go back to basics to address the question directly. We believe that the answer can best be understood in terms of five important and distinctly different roles that a representation plays, each of which places different and, at times, conflicting demands on the properties a representation should have. ...

What Is a Knowledge Representation?

Role 1: A Knowledge Representation Is a Surrogate

First, a knowledge representation is most fundamentally a surrogate, a substitute for the thing itself, that is used to enable an entity to determine consequences by thinking rather than acting, that is, by reasoning about the world rather than taking action in it.

[Modelo, Abstração]

Any intelligent entity that wants to reason about its world encounters an important, inescapable fact: Reasoning is a process that goes on internally, but most things it wants to reason about exist only externally.

[Identificar o que ainda está implícito dentro do conhecimento que já foi explicitado mas que existe no mundo real]

How close is the surrogate to the real thing? What attributes of the original does it capture and make explicit, and which does it omit? Perfect fidelity is, in general, impossible, both in practice and in principle.

All other representations are inaccurate; they inevitably contain simplifying assumptions and, possibly, artifacts.

[Modelos são versões simplificadas da realidade quando representam objetos do mundo real]

Two important consequences follow from the inevitability of imperfect surrogates. One consequence is that in describing the natural world, we must inevitably lie, by omission at least.

[Quanto maior a cobertura maior a imprecisão]

The second and more important consequence is that all sufficiently broad-based reasoning about the natural world must eventually reach conclusions that are incorrect, independent of the reasoning process used and independent of the representation employed. Sound reasoning cannot save us: If the world model is somehow wrong (and it must be), some conclusions will be incorrect, no matter how carefully drawn. A better representation cannot save us: All representations are imperfect, and any imperfection can be a source of error.

[Por mais que a representação inclua contexto ainda é possível que não seja completa e por isso imprecisa]

Role 2: A Knowledge Representation Is a Set of Ontological Commitments

Second, it is a set of ontological commitments, that is, an answer to the question, In what terms should I think about the world?

[Tornar conhecimento tácito em explícito e aplicar um determinado olhar/foco]

If, as we argue, all representations are imperfect approximations to reality, each approximation attending to some things and ignoring others, then in selecting any representation, we are in the very same act unavoidably making a set of decisions about how and what to see in the world.

[A representação escolhida irá destacar alguns aspectos e "apagar" outros]

These commitments and their focusing blurring effect are not an incidental side effect of a representation choice; they are of the essence: A knowledge representation is a set of ontological commitments. I

... the essential information is not the form of this language but the content, that is, the set of concepts offered as a way of thinking about the world. Simply put, the important part is notions such as connections and components, ...

[Foco no que está sendo representado e não em como. Mas o como pode dar mais poder de representação ao modelo escolhido]

Rule-based systems view the world in terms of attribute-object-value triples and the rules of plausible inference that connect them, while frames have us thinking in terms of prototypical objects. Thus, each of these representation technologies supplies its own view of what is
important to attend to, and each suggests, conversely, that anything not easily seen in these terms may be ignored.

[Rules x Frames. Frames se parecem mais com Banco de Dados pq pode ser armazenados como registros em um tabela com todos os atributos (filler) de uma entidade(slot)]

Reminder: A Knowledge Representation Is Not a Data Structure

Note that at each layer, even the first (for example, selecting rules or frames), the choices being made are about representation, not data structures. Part of what makes a language representational is that it carries meaning (Hayes 1979; Brachman and Levesque 1985); that is, there is a correspondence between its constructs and things in the external world. In turn, this correspondence carries with it a constraint.

A semantic net, for example, is a representation, but a graph is a data structure. They are different kinds of entity, even though one is invariably used to implement the other, precisely because the net has (should have) a semantics. This semantics will be manifest in part because it constrains the network topology: A network purporting to describe family memberships as we know them cannot have a cycle in its parent links, but graphs (that is, data structures) are, of course, under no such constraint and can have arbitrary cycles.

[KG não são só estruturas de dados em grafos, são KB do tipo semantic network pois possuem semântica]

Role 3: A Knowledge Representation Is a Fragmentary Theory of Intelligent Reasoning

Third, it is a fragmentary theory of intelligent reasoning expressed in terms of three components: (1) the representation’s fundamental conception of intelligent reasoning, (2) the set of inferences that the representation sanctions, and (3) the set of inferences that it recommends.

[Inferencia no sentido de gerar mais conhecimento]

What Is Intelligent Reasoning?

One view, historically derived from mathematical logic, makes the assumption that intelligent reasoning is some variety of formal calculation, typically deduction; the modern exemplars of this view in AI are the logicists. A second view, rooted in psychology, sees reasoning as a characteristic human behavior and has given rise to both the extensive work on human problem solving and the large collection of knowledge-based systems.

[Tem outras visões ...]

Role 4: A Knowledge Representation Is a Medium for Efficient Computation

Fourth, it is a medium for pragmatically efficient computation, that is, the computational environment in which thinking is accomplished. One contribution to this pragmatic efficiency is supplied by the guidance that a representation provides for organizing information to facilitate making the recommended inferences.

[Reusar esse conhecimento com apoio computacional na automatização de tarefas]

From a purely mechanistic view, reasoning in machines (and, perhaps, in people) is a computational process. Simply put, to use a representation, we must compute with it. As a result, questions about computational efficiency are inevitably central to the notion of representation.

[Eficiência e Efiácia]

Traditional semantic nets facilitate bidirectional propagation by the simple expedient of providing an appropriate set of links, while rule-based systems facilitate plausible inferences by supplying indexes from goals to rules whose conclusion matches (backward chaining) and from facts to rules whose premise matches (forward chaining).

[A propagação em um modelo de grafos se dá através do caminho, ou seja, sequencia de arestas entre os nós]

Role 5: A Knowledge Representation Is a Medium of Human Expression

Fifth, it is a medium of human expression, that is, a language in which we say things about the world.

[Somos seres de linguagens, acesso ao simbólico]

Finally, knowledge representations are also the means by which we express things about the world, the medium of expression and communication in which we tell the machine (and perhaps one another) about the world. This role for representations is inevitable as long as we need to tell the machine (or other people) about the world and as long as we do so by creating and communicating representations. Thus, the fifth role for knowledge representations is as a medium of expression and communication for our use.

[Comunicar, transmitir conhecimento, ensinar]

In turn, this role presents two important sets of questions. One set is familiar: How well does the representation function as a medium of expression? How general is it? How precise? Does it provide expressive adequacy? and so on.

[Como avaliar o KG em termos de precisão e expressividade]

An important question that is discussed less often is, How well does it function as a medium of communication? That is, how easy is it for us to talk or think in this language? What kinds of things are easily said in the language, and what kinds of things are so difficult that they are pragmatically impossible?

[Como avaliar o KG como ferramenta de comunicação? Usar em tarefas de busca seria uma forma?]

Consequence for Practice: Characterizing the Spirit of a Representation

Second, such characterizations would facilitate the appropriate use of a representation. By appropriate, we mean using it in its intended spirit, that is, using it for what it was intended to do, not for what it can be made to do.

[Qual foi a motivação de construção do KG? Ele atende a esse propósito?]

Consequence for Research: Representation and Reasoning Are Intertwined
Consequence for Research: Combining Representations
Consequence for Research: Arguments about Formal Equivalence

"There is a familiar pattern in knowledge representation research in which the description of a new knowledge representation technology is followed by claims that the new ideas are, in fact, formally equivalent to an existing technology."

[Isso explica pq dizem q KG seria equivalente a redes semânticas]

Consequences for Research: All Five Roles Matter

Pragmatically efficient computation matters because most of the use of a representation is (by definition) in the average case.
Interest in producing weaker representations to guarantee improved worst-case performance may be misguided, demanding far more than is necessary and paying a heavy price for it.

[Expressividade não seria mais importante que eficência computacional considerando o viés pragmático]

The Goal of Knowledge Representation Research

We believe that the driving preoccupation of the field of knowledge representation should be understanding and describing the richness of the world.

Summary

We suggest that representation technologies should not be considered as opponents to be overcome, forced to behave in a particular way, but instead, they should be understood on their own terms and used in ways that rely on the insights that were their original inspiration and source of power.