=Paper=
{{Paper
|id=Vol-2937/paper2
|storemode=property
|title=Towards a Declarative Approach to Constructing Dialogue Games
|pdfUrl=https://ceur-ws.org/Vol-2937/paper2.pdf
|volume=Vol-2937
|authors=Mark Snaith,Simon Wells
}}
==Towards a Declarative Approach to Constructing Dialogue Games==
https://ceur-ws.org/Vol-2937/paper2.pdf
Towards a Declarative Approach to Constructing
Dialogue Games
Mark Snaith1 , Simon Wells2
1
Robert Gordon University, Garthdee House, Garthdee Road, Aberdeen, AB10 7QB, Scotland, UK
2
Edinburgh Napier University, Merchiston Campus, Edinburgh, EH10 5DT, Scotland, UK
Abstract
In this paper we sketch a new approach to the development of dialogue games that builds upon the
knowledge gained from several decades of dialogue game research across a variety of communities and
which leverages the capabilities of the Dialogue Game Description Language as a means to describe the
constituent parts of dialogue games. Our ultimate aim is to produce a method for rapidly describing
and implementing games that conform to the designer’s needs by declaring what is required and then
automatically constructing the game from components, called ‘fragments’, that are distilled from existing
dialogue games.
1. Introduction & Motivation
Dialogue games are generally designed to fulfil a specific purpose, for example, modelling
a specific type of dialogue such as the deliberation dialogue game of McBurney et al [6], or
investigating specific contexts of argumentation or dialogue as illustrated in the sequence of
elaborations of game rules for prohibiting the fallacy of Petitio Principii as found in the dialogue
of papers between Woods & Walton [19, 20, 21] on the one hand and of Mackenzie [4, 5] on
the other. A marked feature of this approach was that once the wider set of performatives
was chosen, much of the investigation focused upon small changes to individual constituent
rules. A similar approach has happened over the intervening years as various challenges in
dialogue modelling for agent communication, legal argument, educational interaction, and
policy formulation have been investigated. This has gone beyond specific types of dialogue as
envisaged by Walton and Krabbe [12] to encompass specific areas of human activity, whether
educational dialogue games such as Ravenscroft’s ‘CTG’ [8] and Yuan’s ‘DE’ [22] or the coaching
games of Snaith et al [11]. In each context a specific problem is identified, and a dialogue game
that codifies the interaction dynamics of the situation is produced, often in combination with
wider theoretical contributions. This is not to belittle these very valuable contributions that
have shed light on many aspects of dialogical interaction. Rather we propose that this exact
progress has put us in the position of being able to target a wide range of characteristic dialogue
types, identify games for each of those types, and locutions and rules within those games which
CMNA’21: Workshop on Computational Models of Natural Argument, September 2-3, 2021, Online
Envelope-Open m.snaith@rgu.ac.uk (M. Snaith); s.wells@napier.ac.uk (S. Wells)
GLOBE https://www3.rgu.ac.uk/dmstaff/snaith-mark (M. Snaith); https://www.simonwells.org (S. Wells)
Orcid 0000-0002-0877-7063 (M. Snaith); 0000-0003-4512-7868 (S. Wells)
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pertain to a broad range of dialogical contexts of interaction. A standard way to design and
develop dialogue games has involved the selection of an appropriate set of locutions, often from
an existing and well understood game, then specialising those locutions to the new context. DC
[4] has been a popular basic framework for such research and has yielded specialised variations
such as Yuan’s aforementioned game ‘DE’. Additionally there have been two other threads
of dialogue game research that are important and relate variously to testing games and to
describing them. Firstly the investigation of desiderata [7] and ‘Drosophila’ [15] for evaluating
and testing dialogue games according to various criteria and standards. Secondly, the design
of description languages for producing executable specifications of dialogue games and the
development of game agnostic dialogue run-times for executing game specifications. Together
these approaches enable us to describe, in a consistent and verifiable way, the rules for a specific
game, because of the description language, and then to evaluate that game, either by how
well the game satisfies a given set of criteria (identified through appropriate desiderata), or by
how well the game performs in a given scenario (identified by an appropriate ‘Drosophila’),
where criteria and scenario both match the design goals for the game. Existing games provide
a useful set of starting rules, locution sets, and permissible or prohibited behaviours, work
on desiderata provides useful benchmarks for evaluation, and work on description languages
provides a method of unambiguous description and execution. This paper lays the foundations
for an approach to dialogue game design and construction that builds upon insights from all
of this previous work and seeks to both learn from and integrate these approaches whilst also
imposing a more user friendly declarative approach to game construction. Two key aspects of
this approach are to make the construction of dialogue games declarative, and to reuse suitably
abstracted fragments of existing games as templates, to scaffold the generation of new games
rapidly, accurately, and on demand by non-experts - for example, to underpin interactions in
systems for conversational AI [1]. The remainder of this paper is organised as follows: Section
2 discusses related work, Section 3 describes how DGDL can be re-purposed as the foundation
for a dialogue rule fragment library and introduces elements of a game design and construction
methodology, Section 4 illustrates the proposed process using an existing game from a coaching
scenario, and finally Section 5 reflects upon this approach and describes some directions for
future work.
2. Background & Related Work
A related approach is the Lightweight Coordination Calculus (LCC) due to Robertson [10].
Whilst this approach shares some of our ideals in generating flexible and (semi-)automated
communication protocols, it is a low level approach that is well suited to software agent
coordination, but omits the focus on norm-oriented human communication that characterises
much of dialogue game research, favouring an agent centred role that attempts to bridge between
computational process communication and multi-agent institutions. A second early relevant
approach was the effort to do run-time negotiation of the semantics of agent communication
protocols [9]. This made an important contribution to the concept of protocol as a constructed
object within a shared space as well as the idea that communication protocol is fungible.
Finally a more recent approach to designing and implementing dialogue games can be seen in
ProtOCL [23] which exploits the unified modelling language (UML) and the Object Constraint
Language (OCL), technologies that are more commonly used to design and implement Object
Oriented software systems. In ProtOCL, dialogue games are specified using a series of annotated
diagrams which describe facets of the desired dialogue system. Code, in the form of a Java
Object hierarchy is generated and incorporated into a wider software system. Both the LCC and
the negotiating semantics approaches will likely form a basis for further work that exploits our
proposed fragment library, especially in extending the system towards automated use by agents,
however for the moment we are focusing upon dialogue game development as an essentially
human-centric design activity akin to the ProtOCL approach.
3. Dialogue Fragments & the DGDL
This approach to dialogue description exploits the functionality of the Dialogue Game Descrip-
tion Language (DGDL) [17]. In this section we give a high level overview of the DGDL before
focusing upon game descriptions expressed in the DGDL before finally investigating how such
descriptions can be taken apart to form “dialogue fragments”.
3.1. DGDL
The DGDL is a domain specific language for describing the rules of dialogues games in a format
that can be executed on a dialogue management run-time (such as DGEP [2] or Adamant [14]).
This way a single language can be used to describe a flexible and diverse multiplicity of games
which can then be selected at run-time (rather than compile or design time). This avoids the
need to create a novel implementation each time a new game is devised, but also provides a
route towards implementation for non-programmers. The DGDL is founded upon an extended
Backus-Naur Form (EBNF) grammar [18] that enables games to be described in a way that is
expressive, accounting for a wide variety of rule types, consistent, so that game descriptions are
cohesive, and syntactically verifiable, so that each description can be relied upon to be correctly
expressed within the bounds of the DGDL. The DGDL essentially enables the participants of
the game to be identified, the turn structure to be specified, the stores of artefacts generated
during the dialogue to be designated, and for the rules and interactions to be formulated. Note
that rules and interactions are very similar, they define a set of requirements that must hold and
a consequent set of effects to apply but they differ only in how they are applied. Interactions
describe moves that are explicitly made by a participant during their turn whereas rules are
applied on either a turn-wise or a move-wise basis irrespective of the interactions associated
with a given turn or move. The distinction can be seen in the check for a termination condition,
regardless of the move made, after each turn a check is made on whether a given win-loss
condition holds.
3.2. DGDL game descriptions
We’ll not reproduce the entire grammar here, for reasons of space, but a minimal valid game
description for a game named ‘Simple’ from [13] is illustrated in figure 1. In Simple there are
two players, labelled ‘Player1’ and ‘Player2’, who each possess a public artefact store that is
Simple{
{turns,magnitude:single,ordering:strict}
{players,min:2,max:2}
{player,id:Player1}
{player,id:Player2}
{store,id:CStore,owner:Player1,structure:set,visibility:public}
{store,id:CStore,owner:Player2,structure:set,visibility:public}
{Assert,{p},‘‘I assert that’’,{store(add, {p}, CStore, Speaker)}}
}
Figure 1: An example two player dialogue game called ‘Simple’ described in the DGDL.
structured as a set of artefacts. Each turn the players may make a single move with a strictly
alternating turn structure. There is a single move available to the players, the assert move,
which enters the asserted statement into the artefact store of the speaker. Most dialogue games
are more complex than this. Whilst the specification of players and turns is generally similar,
most games define a rich set of interactions for the players to make, rather than the single
‘Assert’ move in the example, and a diverse set of effects, in terms of game artefacts, to apply
once those moves have been made. Note however that there is a conceptual and practical
difference between the DGDL grammar and a DGDL description. The grammar defines an
abstract space of possible games whilst a DGDL description defines a single, specific, concrete
game that exists within that space. It is the interval between abstract grammar and concrete
game rule that we seek to exploit in this work.
3.3. Deconstructing DGDL descriptions into fragments
Rather than an entire game description we desire fragments of a game that encapsulate an
entire design concept from the source game and which are suitable for reconstructing into
entirely new games. This introduces a notion of portability of rules between DGDL described
games. If a given game implements a particular set of rules, which would be useful to include in
another game, in order to make the same behaviour available in that other game, then fragments
are one element of a means to achieve this. A basic fragment is a valid DGDL expression,
starting from any valid left-hand-side (LHS) grammar rule, rather than merely the start rule, and
completing it through to it’s terminal values. Whereas a ‘DGDL game description’ describes
an entire game, a fragment describes only a part of a game. So all fragments are syntactically
valid sub-expressions of the DGDL grammar. Because such basic fragments are particular to
specific games, in order to make them more flexible, elements of a fragment can be replaced
with their equivalents from the DGDL grammar originating from the same LHS starting point
to yield a semi-instantiated ‘template fragment’. So, for example, where a fragment might
refer, in it’s concrete instance, to a specific effect, e.g. “{store(add, {p}, CStore, Speaker)}” this
could be replaced with the “RuleBody” grammar declaration to indicate that all other aspects
of the fragment should remain the same but that different rule bodies could be applied, for
example, a different artefact store effect. The idea is to provide an intermediate step between
the two extremes of the highly abstract and incomplete grammar level rules and the completely
concrete game description expressions. These intermediate states are our abstract fragments
One or more fragments may be collected together to define a dialogical behaviour context. We
desire to be able to take a declaration such as “prohibit circular reasoning” and then to generate
games which fulfil this criterion on the basis of existing DGDL fragments. Note that this will be
extremely difficult to completely achieve automatically and without error but provides a route
towards more flexible, on the fly, dialogue protocol generation that accounts directly for the
discoveries and achievements in dialogue game research over past decades. Fragments from
multiple different dialogue games can be brought together to form a single library. The intuition
is that games which have been decomposed into fragments can subsequently be recombined to
form new games based upon the desired characteristics of the new game. A fragment library
will comprise a database of fragments from existing dialogue games together with an interface
for assembling fragments into new games.
3.4. Elements of a Process for Constructing Dialogue Games from Fragments
Assuming a library of game fragments, suitably represented as templates for further specialisa-
tion in specific generated games, let’s now consider the process of developing a new game from a
more declarative perspective. The goal is to be able to describe what we want our dialogue game
to do in terms of the characteristics of the resulting game. We propose that much of this process
would be performed in a specialised game development UI whose input was a description of the
desired game and whose output is a valid and fully-formed DGDL document. A variety of user
interfaces could be envisaged from a GUI that enables the user to describe their needs using
standard GUI widgets (selections, drop-downs, text inputs, and whatnot). Various forms of
text-based UI could also be envisaged, including a traditional application programming interface
(API) or, fittingly, a conversational interface, perhaps in the spirit of the recently announced
GitHub co-pilot tool. A starting place is to define a minimal, archetypal set of locutions that
conform to each supported dialogue type and which scaffold the construction of the remainder
of the game. We name such a set of locutions the base game for dialogue type n. The base game
is a starting place, and the addition of rules to it leads to a specific derived game. If more than
one dialogue type is selected then there are two further organisational models that can account
for how the games work together. The first uses a Walton style shift model to move between
dialogue instances, and the second uses a compound model in which the locutions for each
dialogue type are amalgamated into a single whole. There are benefits to each approach and
both are supported by the DGDL. Once a base game has been selected, the user is instructed to
select desirable properties for their game. For example, prohibiting, prescribing, or permitting
specific behaviours. Each supported property will correspond to either an existing fragment, or
else will require a new rule to be defined (in which case the new rule becomes a fragment in
the library for subsequent reuse. At this point a DGDL description can be generated. In order
to determine whether the resulting game is sound automated testing of the game is performed
applying a mixture of desiderata/properties measurement, Drosophila/scenario based testing,
and a form of arguing agent competition [16]. After testing, the game can be imported to a
DGDL run-time such as the Dialogue Game Execution Platform (DGEP) [2] or A DiAlogue
MANagement Tool (ADAMANT) [14].
𝐶 ∈ 𝜒 can justify a goal (𝐽 𝑢𝑠𝑡𝑖𝑓 𝑦), revise a goal (𝑅𝑒𝑣𝑖𝑠𝑒), challenge a goal (𝐶ℎ𝑎𝑙𝑙𝑒𝑛𝑔𝑒), or
accept a goal (𝑎𝑐𝑐𝑒𝑝𝑡):
1. 𝐽 𝑢𝑠𝑡𝑖𝑓 𝑦(𝑔, 𝑟) when they justify the goal 𝑔 with reason 𝑟
LR1
2. 𝑅𝑒𝑣𝑖𝑠𝑒(𝑔, 𝑔 ′ ) when they revise the goal 𝑔 to new goal 𝑔 ′
3. 𝐶ℎ𝑎𝑙𝑙𝑒𝑛𝑔𝑒(𝑔) when they challenge a goal 𝑔 proposed by another coach, or the patient
4. 𝐴𝑐𝑐𝑒𝑝𝑡(𝑔) when they accept a goal 𝑔 proposed by a patient
𝐿𝐶, in addition to those locutions available to all coaches, can propose a goal (𝑃𝑟𝑜𝑝𝑜𝑠𝑒):
LR2
1. 𝑃𝑟𝑜𝑝𝑜𝑠𝑒(𝑔) when they propose the goal 𝑔
𝑃 can accept a goal (𝐴𝑐𝑐𝑒𝑝𝑡) and be unsure about a goal (𝑈 𝑛𝑠𝑢𝑟𝑒):
1. 𝐴𝑐𝑐𝑒𝑝𝑡(𝑔) when they accept a goal 𝑔
LR3
2. 𝑈 𝑛𝑠𝑢𝑟𝑒(𝑔) when they are unsure about a goal 𝑔
3. 𝑅𝑒𝑣𝑖𝑠𝑒(𝑔, 𝑔 ′ ) when they revise the goal 𝑔 to a new goal 𝑔 ′
Table 1
GSDG Locution rules
4. Worked Example
Here, we motivate our proposed Dialogue Fragment Library by showing how an existing
dialogue game can be broken down into fragments of certain dialogue types. Our intention with
this example is to demonstrate that 1) a domain-specific dialogue game consists of more general
sets of locutions and rules; and 2) the game itself could have originally been constructed from
such fragments. For the sake of space, we will not provide the DGDL fragments themselves, but
will instead leave their specifications implicit. We use the goal-setting dialogue game (GSDG)
specified in [11]. Goal-setting is a common technique used in behaviour change, where one
or more coaches (experts) engage with a patient to help them towards an achievable goal (e.g.
a number of daily exercise minutes) [3]. A dialogue based on GSDG is between at least two
participants: a “lead coach” (𝐿𝐶) with expertise in the area in which the goal is being set, e.g.
physical activity, and a patient (𝑃). All other (optional) participants are “coaches” (𝐶1 … 𝐶𝑛 ) with
expertise differing from that of 𝐿𝐶 (e.g. diet, cognitive etc.). The locution and structural rules of
GSDG, shown in Tables 1 and 2 respectively, contain elements of persuasion and negotiation.
A dialogue begins with 𝐿𝐶 proposing a goal, which 𝑃 can either 𝑎𝑐𝑐𝑒𝑝𝑡 or be 𝑢𝑛𝑠𝑢𝑟𝑒 about.
Acceptance by 𝑃 terminates the dialogue, whereas expressing uncertainty continues the process,
which includes 𝐿𝐶 being able to justify the goal (persuasion), or 𝑃 and 𝐿𝐶 repeatedly providing
counter-proposals until a mutually-agreeable goal is found (negotiation). A final element is the
ability for another coach (𝐶) to themselves query the goal proposed by 𝐿𝐶 if 𝑃 has expressed
uncertainty. We now demonstrate how GSDG can be deconstructed into smaller dialogue
fragments.
4.1. Simple persuasion game
The basic structure of GSDG is a simple asymmetric persuasion game between only the lead
coach and the patient. If we were to generalise this persuasion game, with 𝑃1 (“player 1”) taking
the place of lead coach and 𝑃2 taking the place of the patient, we have the following structure
(where the steps are followed in sequence, unless stated):
SR1 All players can perform only one move per turn
SR2 𝐿𝐶 moves first with 𝑃𝑟𝑜𝑝𝑜𝑠𝑒(𝑔)
SR3 After 𝐿𝐶 performs 𝑃𝑟𝑜𝑝𝑜𝑠𝑒(𝑔), 𝑃 can perform: (1) 𝑎𝑐𝑐𝑒𝑝𝑡(𝑔), or (2) 𝑈 𝑛𝑠𝑢𝑟𝑒(𝑔)
SR4 After 𝑃 performs 𝑈 𝑛𝑠𝑢𝑟𝑒(𝑔), 𝐶 ∈ 𝜒 ⧵ {𝐶1 }, where 𝐶1 is the (possibly Lead) Coach to
whom 𝑃 responded, can perform: (1) 𝐶ℎ𝑎𝑙𝑙𝑒𝑛𝑔𝑒(𝑔); or 𝐶1 can perform (1) 𝐽 𝑢𝑠𝑡𝑖𝑓 𝑦(𝑔, 𝑟)
SR5 After 𝐶 ∈ 𝜒 ⧵ {𝐶1 } performs 𝐶ℎ𝑎𝑙𝑙𝑒𝑛𝑔𝑒(𝑔), where 𝐶1 is the (possibly Lead) Coach to
whom the challenge is aimed, 𝐶1 can perform: (1) 𝐽 𝑢𝑠𝑡𝑖𝑓 𝑦(𝑔, 𝑟), or (2) 𝑅𝑒𝑣𝑖𝑠𝑒(𝑔, 𝑔 ′ )
SR6 After 𝐶1 performs 𝐽 𝑢𝑠𝑡𝑖𝑓 𝑦(𝑔, 𝑟), 𝐶 ∈ 𝜒 ⧵ {𝐶1 } can perform: (1) 𝐶ℎ𝑎𝑙𝑙𝑒𝑛𝑔𝑒(𝑟), or (2)
𝑅𝑒𝑣𝑖𝑠𝑒(𝑔, 𝑔 ′ ); or 𝑃 can perform: (1) 𝐴𝑐𝑐𝑒𝑝𝑡(𝑔), or (2) 𝑅𝑒𝑣𝑖𝑠𝑒(𝑔, 𝑔 ′ )
SR7 After 𝐶 ∈ 𝜒 performs 𝑅𝑒𝑣𝑖𝑠𝑒(𝑔, 𝑔 ′ ), 𝑃 can perform: (1) 𝐴𝑐𝑐𝑒𝑝𝑡(𝑔 ′ ), or (2) 𝑈 𝑛𝑠𝑢𝑟𝑒(𝑔 ′ ); or
𝐶1 ∈ 𝜒 ⧵ {𝐶} can perform: (1) 𝐶ℎ𝑎𝑙𝑙𝑒𝑛𝑔𝑒(𝑔 ′ )
SR8 After 𝑃 performs 𝑅𝑒𝑣𝑖𝑠𝑒(𝑔, 𝑔 ′ ), 𝐶 ∈ 𝜒 can perform: (1) 𝐴𝑐𝑐𝑒𝑝𝑡(𝑔 ′ ), or (2) 𝑅𝑒𝑣𝑖𝑠𝑒(𝑔 ′ , 𝑔 ′′ )
Table 2
GSDG Structural rules
1. 𝑃1 : 𝑃𝑟𝑜𝑝𝑜𝑠𝑒(𝑔)
2. 𝑃2 : 𝑈 𝑛𝑠𝑢𝑟𝑒(𝑔) → step 3
𝐴𝑐𝑐𝑒𝑝𝑡(𝑔) → terminates
3. 𝑃1 : 𝐽 𝑢𝑠𝑡𝑖𝑓 𝑦(𝑔, 𝑟)
4. 𝑃2 : 𝐴𝑐𝑐𝑒𝑝𝑡(𝑔) → terminates
This game is somewhat trivial, but is nonetheless valid. Notionally, it models a situation
where 𝑃2 can either outright accept a proposal from 𝑃1 , or demand justification. If a justification
is forthcoming, 𝑃2 is obliged to accept the original proposal. We henceforth refer to this simple
protocol as 𝑆𝑃𝐷 (Simple Persuasion Dialogue).
4.2. Adding elements of negotiation
A key principle of goal-setting is that the patient must take ownership of the goal so they are
motivated to achieve it [3]. This is modelled in GSDG by incorporating elements of negotiation,
allowing the patient to propose their own goal via a “𝑅𝑒𝑣𝑖𝑠𝑒” locution, and subsequently allowing
the lead coach to propose a further alternative goal. These exchanges can be isolated from
GSDG and generalised thus:
1. 𝑃2 : 𝑅𝑒𝑣𝑖𝑠𝑒(𝑔, 𝑔 ′ ) → step 2
𝐴𝑐𝑐𝑒𝑝𝑡(𝑔) → terminates
2. 𝑃1 : 𝑅𝑒𝑣𝑖𝑠𝑒(𝑔 ′ , 𝑔 ′′ )
𝐴𝑐𝑐𝑒𝑝𝑡(𝑔 ′ ) → terminates
While this doesn’t represent a complete dialogue game, we do nevertheless name the function-
ality it provides as 𝑆𝑁 𝐸 (Simple Negotiation Exchange). Using 𝑆𝑃𝐷 as our starting point, 𝑆𝑁 𝐸
is incorporated in two places: for 𝑃2 , 𝑅𝑒𝑣𝑖𝑠𝑒 is available as an alternative to 𝐴𝑐𝑐𝑒𝑝𝑡 following a
𝐽 𝑢𝑠𝑡𝑖𝑓 𝑦; for 𝑃1 , 𝑅𝑒𝑣𝑖𝑠𝑒 and 𝐴𝑐𝑐𝑒𝑝𝑡 are then available. 𝑃1 using a 𝑅𝑒𝑣𝑖𝑠𝑒 move effectively triggers
a new dialogue with 𝑔 ′′ as the new topic.
1. 𝑃1 : 𝑃𝑟𝑜𝑝𝑜𝑠𝑒(𝑔)
2. 𝑃2 : 𝑈 𝑛𝑠𝑢𝑟𝑒(𝑔) → step 3
𝐴𝑐𝑐𝑒𝑝𝑡(𝑔) → terminates
3. 𝑃1 : 𝐽 𝑢𝑠𝑡𝑖𝑓 𝑦(𝑔, 𝑟)
4. 𝑃2 : Revise(g, g′ ) → step 5
𝐴𝑐𝑐𝑒𝑝𝑡(𝑔) → terminates
5. 𝑃1 : Revise(g′ , g′′ ) → step 2
𝐴𝑐𝑐𝑒𝑝𝑡(𝑔 ′ ) → terminates
This game, 𝑆𝑃𝐷-𝑆𝑁 𝐸, can be described as follows:
• A game based on 𝑆𝑃𝐷
• Following a 𝐽 𝑢𝑠𝑡𝑖𝑓 𝑦 move from 𝑃1 , 𝑃2 can begin an 𝑆𝑁 𝐸
• If the 𝑆𝑁 𝐸 does not lead to termination, proceed to step 2 (effectively starting a new
𝑆𝑃𝐷-𝑆𝑁 𝐸 albeit without the initial 𝑃𝑟𝑜𝑝𝑜𝑠𝑒 move)
4.3. Third-party challenging
The final aspect of GSDG is another coach being able to challenge the lead coach’s proposed goal.
This challenge differs slightly from that available to the patient (via an 𝑈 𝑛𝑠𝑢𝑟𝑒 move) in that the
𝐶ℎ𝑎𝑙𝑙𝑒𝑛𝑔𝑒 move is available to the other coach if and only if the patient themselves expresses
uncertainty (via an 𝑈 𝑛𝑠𝑢𝑟𝑒 move). This is intended to model the behaviour observed in [11]
where a second coach can challenge 𝐿𝐶’s proposed goal as a way of helping the patient reflect
on whether they wish to propose an alternative. Adding third-party challenging is relatively
trivial insofar as its use does not mandate any new locution types, but it does have an impact
on the overall structure of possible dialogues. Following a 𝐶ℎ𝑎𝑙𝑙𝑒𝑛𝑔𝑒 move, 𝑃1 is permitted to
immediately revise the challenged goal, effectively triggering a new dialogue with the revised
goal as the topic:
1. 𝑃1 : 𝑃𝑟𝑜𝑝𝑜𝑠𝑒(𝑔)
2. 𝑃2 : 𝑈 𝑛𝑠𝑢𝑟𝑒(𝑔) → step 3 or 4
𝐴𝑐𝑐𝑒𝑝𝑡(𝑔) → terminates
3. P3 : Challenge(g)
4. 𝑃1 : 𝐽 𝑢𝑠𝑡𝑖𝑓 𝑦(𝑔, 𝑟) → step 5
Revise(g, g′ ) (if 𝑃3 moved 𝐶ℎ𝑎𝑙𝑙𝑒𝑛𝑔𝑒) → step 2
5. 𝑃2 : 𝑅𝑒𝑣𝑖𝑠𝑒(𝑔, 𝑔 ′ ) → step 6
𝐴𝑐𝑐𝑒𝑝𝑡(𝑔) → terminates
6. 𝑃1 : 𝑅𝑒𝑣𝑖𝑠𝑒(𝑔 ′ , 𝑔 ′′ ) → step 2
𝐴𝑐𝑐𝑒𝑝𝑡(𝑔 ′ ) → terminates
This modified version of 𝑆𝑃𝐷-𝑆𝑁 𝐸 can be described as follows:
• A game based on 𝑆𝑃𝐷-𝑆𝑁 𝐸 with an additional participant 𝑃3
• Following an 𝑈 𝑛𝑠𝑢𝑟𝑒 move from 𝑃2 , 𝑃3 can perform a 𝐶ℎ𝑎𝑙𝑙𝑒𝑛𝑔𝑒 move, after which 𝑃1 can
𝐽 𝑢𝑠𝑡𝑖𝑓 𝑦 or 𝑅𝑒𝑣𝑖𝑠𝑒, and the dialogue continues per the existing rules of 𝑆𝑃𝐷-𝑆𝑁 𝐸
4.4. Summary
The aim of this worked example has been to show that an existing domain-specific dialogue game,
GSDG can be deconstructed into fragments consisting of more general dialogical interactions
and that, in principle, the game could have been constructed from those fragments in the first
place. Underpinning GSDG are three distinct elements: a simple persuasion game (𝑆𝑃𝐷), a
simple negotiation exchange (𝑆𝑁 𝐸), and third-party challenging. Individually, none of these are
intrinsically linked to goal-setting; it is in combining them we arrive at a dialogue game that
models the theoretical behaviour of goal-setting.
5. Discussion & Future Work
We’ve sketched out how the DGDL can form the central scaffold for a declarative approach to
game development that builds upon and exploits much previous work. Key questions remain
regarding the degree to which we’ve explored the possible space of dialogue games, how well
the DGDL supports complete exploration of that space, and how many rules and behaviours
have been encoded into DGDL expressions. It remains unclear to what degree existing rules
can be recombined automatically, but we are committed to the idea that we should be learning
from, and building upon, the lessons from existing dialogues games. It’s also unclear to what
degree automated testing of new games can be sound and exhaustive. However, for the first
time, it appears that the key pieces to enable an advance in dialogue game design, construction,
testing, and deployment are in place, potentially enabling wider exploitation of this approach
to dialogue research within the wider conversational AI agenda,.
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