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Joe Corneli tweak recommendations and future work about 9 years ago

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publisher={Wiley Online Library} } @incollection{von2003cybernetics, title={Cybernetics of cybernetics}, author={Von Foerster, Heinz}, booktitle={Understanding Understanding}, pages={283--286}, year={2003 [1979]}, publisher={Springer} } @book{von2003essays, title={{U}nderstanding {U}nderstanding: {E}ssays on {C}ybernetics and {C}ognition}, author={von Foerster, Heinz},

This diagram does Here we do not mean to suggest that every instance of ``a solution to a problem in a context'' is due to serendipity at work -- on the contrary, that is just the discovery step. Inventing a viable design pattern only happens when the solution is explicable and useful. To van Andel's assertion that ``The very moment I can plan or programme `serendipity' it cannot be called serendipity anymore'' -- of course, if the context is fully determined in advance, and if the solution is completely replicable, then some of the fundamental conditions for serendipity are not met. However, anymore,'' we would reply that can also describe patterns (and programs) with built-in indeterminacy: indeterminacy. Here is one of van Andel's patterns of serendipity rewritten as a design pattern using the template suggested by our model: \begin{mdframed} \vspace{-.35cm} \paragraph{Successful error} \emph{Van Andel's example} -- Post-it\texttrademark\ Notes\\[.05cm] \begin{description} \item[{\tt context}] -- You run a creative organisation with several different divisions and many contributors with different expertise.Unexpected discoveries are often made. \item[{\tt problem}] -- One of the members of your organisation discovers something with interesting properties, butthat no one knows how to turn it into a product with industrial or commercial application. \item[{\tt solution}] -- You create a space for sharing and discussing interesting ideas on an ongoing basis (perhaps a Writers Workshop). \item[{\tt rationale}] -- You suspect it's possible that one of the

application; you know that if a potential application is found, it may not be directly marketable, but at least there will be a prototype that can be concretely discussed. \item[{\tt resolution}] -- Writing down and promulgating the The \emph{Successful error} pattern rewritten using this template gives one is itself an example of such a prototype. \end{description} \end{mdframed}

\subsection{Future Work} \label{sec:futurework} \label{sec:hatching} Within the context of the ongoing COINVENT project \cite{coinvent14}, we are interested in using computational theory blending to realise certain aspects of this model in As astand-alone architecture. % It will be useful to consider how we can take both the \emph{discovery step}, which combines a serendipity trigger $T$, and prior preparation $p$, to produce a classification $T^{\star}$ -- and the \emph{invention step}, which combines the classified trigger $T^{\star}$, and preparations $p^{\prime}$, and produces a novel result $R$ -- to be \emph{blends} in the sense of Joseph Goguen \citeyear{goguen1999introduction}. The epistemological frameworkof discovery gives some important clues about how to compute a common base between $T$ and $p$, a key step for blending, since these common features will typically be preserved in the blend. Although $T$ was previously uninteresting, it will have attributes or attribute-types that match the patterns recognised by $p$ (e.g. van Andel's \citeyear{van1994anatomy} \emph{One surprising observation}). % In managing the invention step, reasoning, experimentation, social interaction strategies rely on $p^{\prime}$, which might draw on patterns like van Andel's \emph{Successful error} in order to pinpoint the seeds processes ofa useful result within $T^{\star}$. One important guidepost for implementation is the theory-building orientation that says that outcomes may include new patterns of behaviour that the system can draw on in subsequent interactions. What is particularly needed is an approach to encoding patterns and methods for pattern discovery in a computationally accessible manner. Here and invention, we are drawn to the approach taken by the \emph{design pattern} community \cite{alexander1999origins}, although we recognize that we would be using propose to use design patterns in rather nonstandard way: \begin{itemize} \item[(1)] We want to encode our design patterns directly in runnable programs, not just give them to programmers as heuristic guidance. \item[(2)] We want the (automated) programmer to generate new design patterns, not just apply or adapt old ones. \item[(3)] We want our design patterns to help describe find new problems, not just capture the solutions to existing problems. ones. \end{itemize} \citeA{meszaros1998pattern} describe the typical scenario for design pattern writers: ``You are an experienced practitioner in your field. You have noticed that you keep using a certain solution to a commonly occurring problem. You would like to share your experience with others.'' They also remark that remark, ``What sets patterns apart is their ability to explain the rationale for using the solution (the `why') in addition describing the solution (the `how').'' Regarding the criteria that pattern writers seek to address, they write: address: ``The most appropriate solution to a problem in a context is the one that best resolves the highest priority forces as determined by the particular context.'' %% Their article describes a number of criteria %% relevant at the meta-level of pattern writing, to writing good design patterns, e.g. \emph{Clear target %% audience}, \emph{Visible forces}, and \emph{Relationship to other %% patterns}. A good design pattern describes \emph{describes} the resolution offorces, but it also resolves certain forces itself. In terms in the target domain; in the setting we're interested in, creating a new design pattern also \emph{effects} a resolution of forces directly. This use case maps into our now-familiar diagram: diagram of the basic features of serendipity as follows: \input{pattern-schematic-tikz.tex}

\subsection{Recommendations} \label{sec:recommendations} Deleuze writes: wrote: ``True freedom lies in the power to decide, to constitute problems themselves'' \cite[p. 15]{deleuze1991bergsonism}; and, elsewhere, rephrasing this sentiment in a social way: \begin{quote} ``\emph{We learn nothing from those who say: `Do as I do'. Our only teachers are those who tell us to `do with me', and are able to emit signs to be developed in heterogeneity rather than propose gestures for us to reproduce.}''~\cite[p. 26]{deleuze1994difference} \end{quote} Dewey emphasised a child's training must deal with objects which ``arise out of their interests and their own problems'' \cite[p. 73]{dewey-by-mead}. Von von Foerster \citeyear[p. 286]{von2003cybernetics} advocated a form of cybernetics \emph{second-order cybernetics} in which ``the observer who enters the system shall be allowed to stipulate his own purpose'' \cite[p. 286]{von2003essays}. purpose.'' % Dewey, Whiteheadis similar too. The Our thought experimentpresented in Section \ref{sec:ww} illustrated explores these ideas, and helps to illustrate the relationship between problem creation and serendipity. Looking The search forthe connections that make raw data into ``strategic data'' is a core pattern part of problem creation. This is this common ground, and an appropriate theme for researchers in computational creativity to grapple with. In \cite{stakeholder-groups-bookchapter}, we outlined a general programme for computational creativity, and examined perceptions of

-- understood as human communities. We should now add a fourth important ``stakeholder'' group in computational creativity research: computer systems themselves. Creativity may look very different to this fourth stakeholder group than it looks to us. When We should give computers are required to the tools effectively evaluate their own results, we are also implicitly requiring them to evaluate results and their creative process.We should give them the tools to do that effectively. % These ideas set a relatively high bar, if only because computational creativity has often been focused on generative rather than reflective

recalling Turing's proposal that computers should ``be able to converse with each other to sharpen their wits'' \cite{turing-intelligent}. Other fields, including computer Chess, Go, and argumentation have achieved such standards, this, and to good effect. The Writers Workshop described in Section \ref{sec:ww} is an example of one such social model, but more fundamentally, it is an example of