In this paper we present an ontology solution to solve the problem of language heterogeneity among negotiating agents during the exchange of messages over Internet. Traditional negotiation systems have been implemented using different syntax and semantics. Our proposal offers a novel solution incorporating an ontology, which serves as a shared vocabulary of negotiation messages; and a translation module that is executed on the occurrence of a misunderstanding. We implemented a service oriented architecture for executing negotiations and conducted experiments incorporating different negotiation messages. The results of the tests show that the proposed solution improves the interoperability between heterogeneous negotiation agents.IFIP International Conference on Artificial Intelligence in Theory and Practice - Integration of AI with other TechnologiesRed de Universidades con Carreras en Informática (RedUNCI

Bravo, Maricela

López, Máximo

Montes, Azucena

Pinto, Raúl

Pérez, Joaquín

Santaolaya, René

English

El Servicio de Difusión de la Creación Intelectual

  
Ontology Support for Translating 
Negotiation Primitives 
Maricela Bravo1, Máximo López1, Azucena Montes1, René Santaolaya1, 
Raúl Pinto1, and Joaquín Pérez1 
1Centro Nacional de Investigación y Desarrollo Tecnológico 
Interior Internado Palmira S/N, Cuernavaca, Mor. 62490, México 
{mari_clau, maximo, amr, rene, rpinto, jperezo}@cenidet.edu.mx, 
WWW home page: http://www.cenidet.edu.mx 
Abstract. In this paper we present an ontology solution to solve the problem 
of language heterogeneity among negotiating agents during the exchange of 
messages over Internet. Traditional negotiation systems have been 
implemented using different syntax and semantics. Our proposal offers a novel 
solution incorporating an ontology, which serves as a shared vocabulary of 
negotiation messages; and a translation module that is executed on the 
occurrence of a misunderstanding. We implemented a service oriented 
architecture for executing negotiations and conducted experiments 
incorporating different negotiation messages. The results of the tests show that 
the proposed solution improves the interoperability between heterogeneous 
negotiation agents. 
1   Introduction 
Negotiation plays a fundamental role in electronic commerce activities, allowing 
participants to interact and take decisions for mutual benefit. Recently there has been 
a growing interest in conducting negotiations over Internet, and constructing large-
scale agent communities based on emergent Web service architectures. The 
challenge of integrating and deploying negotiation agents in open and dynamic 
environments is to achieve effective communications.  
Traditional negotiation systems have been implemented in multi-agent systems 
(MAS), where agents exchange messages using an agent communication language 
(ACL) based on a specification like KQML [1] or FIPA [2]. These specifications 
provide a set of negotiation primitives based on speech act theory, and provide 
semantics for these primitives usage during communication. In order to facilitate 
effective communication, agents must be designed to be compliant with one of these 
2 Maricela Bravo, Máximo López, Azucena Montes, René Santaolaya, Raúl Pinto and 
Joaquín Pérez 
 
ACL specifications. But the implementations of these negotiation primitives in real 
systems, differs in syntax and usage, because is based on proprietary program code 
produced by developers. 
 
The problem of communication between negotiation agents is that even if two 
agents are following the same ACL, they may still suffer misunderstandings due to 
the different syntax and semantics of their vocabularies. In table 1, we can see that 
some of the reported communication languages in negotiation systems are based on 
FIPA, and some use a different ACL not compliant with any particular specification. 
Table 1. Negotiation primitives used in different systems 
Authors ACL Negotiation Primitives 
Jin Baek Kim, Arie 
Segev [7] 
FIPA  
Initial_offer 
RFQ 
Accept 
Reject 
Offer 
Counter-offer 
 
Stanley Y. W. Su, 
Chunbo Huang, 
Joachim Hammer 
[8] 
FIPA CFP 
Propose 
Accept 
Terminate 
Reject 
Acknowledge 
Modify 
Withdraw 
 
Anthony Chavez, 
Pattie Maes [10] 
Uses a predefined 
set of methods, not 
compliant with any 
ACL specification. 
 
accept-offer?(agent, from-agent, offer) 
what-is-price?(agent, from-agent) 
what-is-item?(agent, from-agent) 
add-sell-agent 
add-buy-agent 
add-potential-customers(sell-agent, potential-customers) 
add-potential-sellers(buy-agent, potential-sellers) 
agent-terminated(marketplace, agent) 
deal-made(marketplace, sell-agent, buy-agent, item, 
price) 
 
Sonia V. Rueda, 
Alejandro J. García, 
Guillermo R. Simari 
[11] 
Based on speech 
act theory, not 
compliant with any 
ACL specification. 
Requests_Add(s, h, p) 
Authorize_Add(s, h, p) 
Require(s, h, p) 
Demand(s, h, p) 
Accept(s, h, p) 
Reject(s, h, p) 
Unable(s, h, p) 
Require-for(s, h, p, q) 
Insist_for(s, h, p, q) 
Demand_for(s, h, p, q) 
Ontology Support for Translating Negotiation Primitives 3
 
Haifei Li, Chunbo 
Huang and Stanley 
Y.W Su [12] 
Superset of FIPA  
Call for proposal 
Propose proposal 
Reject proposal 
Withdraw proposal 
 
Accept proposal 
Modify proposal 
Acknowledge message 
Terminate negotiation 
 
Jürgen Müller [6] Based on speech 
act theory, not 
compliant with any 
ACL specification 
 
Initiators: 
Propose, Arrange, 
Request, Inform, 
Query, Command, 
Inspect 
 
 
Reactors: 
Answer, 
Refine, 
Modify, 
Change, Bid, 
Send, Reply, 
Refuse, 
Explain 
 
Completers: 
Confirm, 
Promise, 
Commit, 
Accept, 
Reject, Grant, 
Agree. 
 
To solve the communication problem between heterogeneous agents, we selected 
a translation approach based on the implementation of a shared ontology. In this 
ontology we explicitly describe and classify negotiation primitives in a machine 
interpretable form. Negotiation agents should not be forced to commit to a specific 
syntax. Instead, the ontology provides a shared and public vocabulary that the 
translator module uses to help agents to communicate during negotiation processes. 
We have implemented a negotiation system based on Web services technologies, 
into which we have incorporated the translator module and the shared ontology. Our 
approach acknowledges that agents may use different negotiating languages. 
The rest of the document is organized as follows. In section 2, we present the 
translator architecture. In section 3, we describe the design of the ontology. In 
section 4, the general architecture of the system for executing negotiation processes 
is presented. In section 5, we describe the results of experiments. Finally in section 6, 
we present conclusions. 
2   Architecture of the Translator 
The translator acts as an interpreter of different negotiation agents. In figure 1, we 
present the architectural elements involved in translation. This architecture consists 
of the following elements: multiple negotiation agents, the message transport, the 
translator module, and the shared ontology. Each negotiation agent in turn consists of 
a local ACL, decision making strategies to determine the preferences, and the 
negotiation protocol.  
For example, suppose that agents A and B initiate a negotiation process, using 
their own local ACL, sending messages over the message transport. If happens that 
agent A misunderstands a message from agent B, it invokes the semantic translator 
module sending the message parameters (sender, receiver, message). The translator 
interprets the message based on the definitions of the sender agent and converts the 
message into an interlingua. Then the translator converts the interlingua 
4 Maricela Bravo, Máximo López, Azucena Montes, René Santaolaya, Raúl Pinto and 
Joaquín Pérez 
 
representation to the target ACL based on the receiver agent definitions. Finally 
sends the message back to the invoking agent A and they continue with execution of 
negotiation. The translator is invoked only in the occurrence of a misunderstanding, 
assuring interoperability at run time. 
 
Fig. 1. Translator architecture 
3   Shared Ontology 
The principal objective in designing the ontology was to serve as an interlingua 
between agents during exchange of negotiation messages. According to Müller [6], 
negotiation messages are divided into three groups: initiators, if they initiate a 
negotiation, reactors, if they react on a given statement and completers, whether they 
complete a negotiation. We selected this classification to allow the incorporation of 
new negotiation primitives from the local agent ACL. Figure 2 shows the general 
structure of our ontology. 
Based on the concepts and negotiation primitives we built our ontology. To code 
the ontology we decided to use OWL as the ontological language, because it is the 
most recent development in standard ontology languages from the World Wide Web 
Consortium (W3C)1. An OWL ontology consists of classes, properties and 
individuals. We developed the ontology using Protégé [14, 15], an open platform for 
ontology modeling and knowledge acquisition. Protégé has an OWL Plugin, which 
can be used to edit OWL ontologies, to access description logic reasoners, and to 
acquire instances of semantic markup. 
 
1 http://www.w3.org 
Negotiation agent A: 
Semantic 
Translator 
Shared 
Ontology 
Negotiation agent B: 
Local ACL Local ACL 
Protocol 
Strategy 
Protocol 
Strategy 
Message Transport 
Ontology Support for Translating Negotiation Primitives 5
 
 
 
Fig. 2. General structure of the negotiation ontology 
4   Implementation of the Negotiation System 
The general architecture for the execution of negotiation processes is illustrated in 
figure 4. In this section we briefly describe the functionality and implementation 
techniques for each component. 
 
a. The matchmaker is a Java module which is continuously browsing buyer 
registries and seller descriptions, searching for coincidences. 
b. The negotiation process module is a BPEL4WS-based engine that controls the 
execution of negotiation processes between multiple agents according to the 
predefined protocols. BPEL4WS provides a language for the formal 
specification of business processes and business interaction protocols. The 
interaction with each partner occurs through Web service interfaces, and the 
structure of the relationship at the interface level is encapsulated in what is 
called a partner link. 
c. Seller and buyer agents are software entities used by their respective owners to 
program their preferences and negotiation strategies. For example, a seller 
agent will be programmed to maximize his profit, establishing the lowest 
acceptable price and the desired price for selling. In contrast, a buyer agent is 
seeking to minimize his payment. On designing the negotiation agents, we 
identified three core elements, strategies, the set of messages and the protocol 
for executing the negotiation process. The requirements for these elements 
were specified as follows: 
Shared Ontology 
Participants Language 
Parameters Primitives 
Initiators Reactors Completers 
Decision Protocols 
- Propose 
- Arrange 
- Request 
- Initiate 
- Start 
- … 
- Answer 
- Send 
- Reply 
- Counteroffer 
- Refuse 
- … 
- Confirm 
- Accept 
- Reject 
- End 
- Agree 
- … 
6 Maricela Bravo, Máximo López, Azucena Montes, René Santaolaya, Raúl Pinto and 
Joaquín Pérez 
 
• Strategies should be private to each agent, because they are 
competing and they should not show their intentions. 
• Messages should be generated privately. 
• The negotiation protocol should be public or shared by all agents 
participating, in order to have the same set of rules for interaction. 
The negotiation protocol establishes the rules that agents have to 
follow for interaction. 
 
d. The translator module is invoked whenever the agent misunderstands a 
negotiation message from another agent. The translator module was 
implemented using Jena2, a framework for building Semantic Web 
applications. It provides a programmatic environment for OWL, including a 
rule-based inference engine. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Fig. 3. Architecture of the negotiation system 
5   Experimentation 
In this section we describe the methodological steps that we followed for the 
execution of experiments. 
 
a. Identify and describe negotiation agent’s characteristics 
Table 2 shows the characteristics of agents A and B, specifying their language 
definitions: names of primitives and a description. 
 
2 http://jena.sourceforge.net 
Negotiation 
Process 
Module 
Translator 
Module 
Matchmaker Seller 
Registry 
Buyer 
Registry 
Seller 
Agent 
Buyer 
Agent 
Negotiation 
Process 
Descriptions 
Shared 
Ontology 
Ontology Support for Translating Negotiation Primitives 7
 
Table 2. Characteristics of agents A and B 
Agent A Language definitions 
  
(CFP, “Initiate a negotiation process by calling for proposals”), 
(Propose, “Issue a proposal or a counterproposal”),  
(Accept, “Accept the terms specified in a proposal without further 
modifications”),  
(Terminate, “Unilaterally terminate the current negotiation process”),  
(Reject, “Reject the current proposal with or without an attached 
explanation”),  
(Acknowledge, “Acknowledge the receipt of a message”),  
(Modify, “Modify the proposal that was sent last”),  
(Withdraw, “Withdraw the last proposal”) 
 
Agent B Language definitions 
  
(Initial_offer, “Send initial offer”),  
(RFQ, “Send request for quote”),  
(Accept, “Accept offer”),  
(Reject, “Reject offer”),  
(Offer, “Send offer”),  
(Counter-offer, “Send counter offer”) 
(Withdraw, “Withdraw the last proposal”) 
 
 
b. Classify negotiation primitives in the ontology classes 
For each negotiation primitive we need to analyze its semantics and usage. 
According to this description we can identify to which class it belongs. Table 3 
shows the classification of the primitives provided by agents A and B. 
Table 3. Classification of negotiation primitives 
Agent Starter Reactor Completer 
A (Buyer) CFP Propose 
Modify 
Withdraw 
Acknowledge 
Accept 
Reject 
Terminate 
NotUnderstood 
 
B (Seller) RFQ Initial_Offer 
Offer 
Counter_Offer 
Accept 
Reject 
NotUnderstood 
 
 
c. Align primitives in a finite state machine 
Alignment is necessary to verify and clarify the intended usage of negotiation 
primitives. 
8 Maricela Bravo, Máximo López, Azucena Montes, René Santaolaya, Raúl Pinto and 
Joaquín Pérez 
 
 
Fig. 4. Finite state machine 
d. Identify and establish the relations between different primitives 
Based on the classification of primitives and their allocation in the finite state 
machine, we can identify the relations between negotiation primitives. 
 
A           B 
CFP    isSynonymOf   RFQ 
Propose   isSynonymOf   Offer 
Propose   isSynonymOf   Inicial_Offer 
Modify   isSynonymOf   Counter_Offer 
Withdraw   isSynonymOf   Counter_Offer 
Terminate  isSimilarOf   Reject 
 
e. Publish and code primitives in the ontology 
This step consists of populating the ontology with the primitive’s definitions and 
relations. 
 
f. Execute negotiation 
When primitives have been published, the process of negotiation between these 
agents can be started. We executed 15 negotiation tests with these agents. The results 
of these experiments were registered in a log file. Table 4 shows the results. 
Table 4. Experimental results 
 
Test LastPrice MaxPay Iterations Quantity FinalPrice Result 
1  $  1,750.00  $  1,000.00 12 1500  $            -    Reject 
2  $     774.00   $  1,760.00 3 887  $  1,674.00 Accept 
3  $  1,788.00   $     128.00 12 1660  $            -    Reject 
4  $  1,058.00   $     110.00 12 1270  $            -    Reject 
5  $     761.00   $       77.00 2 1475  $            -    NotUnderstood 
6  $     621.00   $     446.00 12 56  $            -    Reject 
7  $     114.00   $     704.00 7 8  $     614.00 Accept 
A B
A
A 
A 
CFP/RFQ 
Offer/ 
Propose 
Counter_Offer/ 
Modify 
Accept 
Reject 
Ontology Support for Translating Negotiation Primitives 9
 
Test LastPrice MaxPay Iterations Quantity FinalPrice Result 
8  $  1,837.00   $  2,199.00 9 53  $  2,137.00 Accept 
9  $  1,665.00   $  2,047.00 9 56  $  1,965.00 Accept 
10  $  1,920.00   $     286.00 12 81  $            -    Reject 
11  $     172.00   $  1,553.00 2 41  $  1,172.00 Accept 
12  $     980.00   $  1,541.00 2 67  $            -    NotUnderstood 
13  $  1,276.00   $     500.00 2 43  $            -    Reject 
14  $  1,500.00   $  1,108.00 2 110  $            -    NotUnderstood 
15  $  1,400.00   $  1,520.00 3 4 $  1,452.00 Accept 
 
The results of experiments showed that there were some negotiations that ended 
the process with a NotUnderstood message. This was due to the emission of an 
Acknowledge message form agent A, which agent B does not recognize. Although, 
the experiment results show good evidence that the two agents are communicating 
efficiently even when their language definitions are quite different. 
6   Conclusions 
In this paper we have presented how an ontology approach can improve 
interoperability between heterogeneous negotiation agents. In particular we 
incorporated a translator solution for the problem of lack of understanding among 
seller and buyer agents during the exchange of messages at run time. We evaluated 
the ontology in the target application, and described the system architecture into 
which the negotiation processes are executed. We believe that semantic 
interoperability of ACL is an important issue that can be solved by incorporating a 
shared ontology. The experimental tests showed that the proposed architecture 
improves the continuity of the execution of negotiation processes, resulting in more 
agreements. 
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Ontology support for translating negotiation primitives

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Ontology support for translating negotiation primitives

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