Abstract
This paper examines effective knowledge-retrieval heuristics in terms of transactive memory in concurrent software development teams. We propose six knowledge-retrieval heuristics and evaluate their effectiveness in four typical situations encountered by concurrent software development teams. Agent-based social simulation suggests the following findings about effective heuristics in each situation: (1) in large teams, if team members have incomplete information about their teammates’ expertise, both the minimum effort type and the risk aversion type are effective; (2) in small teams, if team members have incomplete information about their teammates’ expertise, the broad retrieval type is effective; (3) in small teams with a heavy work-load, if team members have sufficient information about their teammates’ expertise, the minimum effort type is effective; (4) in small teams with a light work-load, if team members have sufficient information about their teammates’ expertise, both the minimum effort type and the “ask others” type are effective.
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References
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Acknowledgments
This work was supported in part by a Grant-in-Aid for Scientific Research 21310097 of JSPS and a Grant for Special Research Projects of Waseda University (2009B-176).
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Appendices
Appendix: Algorithm of Knowledge-Retrieval Heauristics
Minimum effort type
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1.
Agent \( i\)requests the required knowledge \( k\)from the agent \( {i}^{\prime }\)(\( {i}^{\prime }=\mathrm{arg}\mathrm{max}{\displaystyle {\sum }_{{k}^{\prime }}{}_{i}{C}_{{i}^{\prime }{k}^{\prime }}}\)). Go to 2
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2.
Resolve task \( j\)? (Yes => Task resolution; No => Go to 3)
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3.
\( i\)acquired \( k\)? (Yes => Go to 1; No => Go to 4)
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4.
\( i\)requests \( k\)from \( {i}^{\prime }\)such that \( {}_{i}{C}_{{i}^{\prime }k}=1\). Go to 5
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5.
Resolve \( j\)? (Yes => Task resolution; No => Go to 6)
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6.
\( i\)acquired \( k\)? (Yes => Go to 4; No => Go to 7)
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7.
Execute random type
Risk aversion type
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1.
Agent \( i\)requests agent \( {i}^{\prime }\)’s TM \( {C}_{{i}^{\prime }1},\cdots, {C}_{{i}^{\prime }KS}\)(\( {i}^{\prime }=\mathrm{arg}\mathrm{max}{\displaystyle {\sum }_{{k}^{\prime }}{}_{i}{C}_{{i}^{\prime }{k}^{\prime }}}\)). Go to 2
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2.
Resolve \( j\)? (Yes => Task resolution; No => Go to 3)
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3.
\( i\)requests \( k\)from \( {i}^{\prime }\)(\( {i}^{\prime }=\mathrm{arg}\mathrm{max}{\displaystyle {\sum }_{{k}^{\prime }}{}_{i}{C}_{{i}^{\prime }{k}^{\prime }}}\)). Go to 4
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4.
Resolve j? (Yes => Task resolution; No => Go to 5)
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5.
\( i\)acquired \( k\)? (Yes => Go to 6; No => Go to 7)
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6.
\( {i}^{\prime }\)had knowledge \( k\)? (Yes => Go to 3; No => Go to 1)
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7.
\( i\)requests agent \( {i}^{\prime }\)’s TM \( {C}_{{i}^{\prime }1},\cdots, {C}_{{i}^{\prime }KS}\)from \( {i}^{\prime }\)such that \( {}_{i}{C}_{{i}^{\prime }k}=1\). Go to 8
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8.
Resolve \( j\)? (Yes => Task resolution; No => Go to 9)
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9.
\( i\)requests \( k\)from \( {i}^{\prime }\)such that \( {}_{i}{C}_{{i}^{\prime }k}=1\). Go to 10
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10.
Resolve \( j\)? (Yes => Task resolution; No => Go to 11)
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11.
\( i\)acquired \( k\)? (Yes => Go to 12; No => Go to 13)
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12.
\( {i}^{\prime }\)had knowledge \( k\)? (Yes => Go to 9; No => Go to 7)
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13.
Execute random type
“Ask others” type
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1.
Agent \( i\)requests the required knowledge \( k\)from agent \( {i}^{\prime }\)(\( {i}^{\prime }=\mathrm{arg}\mathrm{max}{\displaystyle {\sum }_{{k}^{\prime }}{}_{i}{C}_{{i}^{\prime }{k}^{\prime }}}\)). Go to 2
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2.
Resolve task \( j\)? (Yes => Go to 12; No => Go to 5)
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3.
\( i\)acquired \( k\)? (Yes => Go to 1; No => Go to 4)
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4.
\( i\)requests \( k\)from \( {i}^{\prime }\)such that \( {}_{i}{C}_{{i}^{\prime }k}=1\). Go to 5
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5.
Resolve task \( j\)? (Yes => Go to 12; No => Go to 6)
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6.
\( i\)acquired \( k\)? (Yes => Go to 4; No => Go to 7)
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7.
\( i\)requests \( {i}^{\prime }\)’s TM \( {}_{{i}^{\prime }}{C}_{1k},\cdots {,}_{{i}^{\prime }}{C}_{ASk}\)from \( {i}^{\prime }\)(\( {i}^{\prime }=\mathrm{arg}\mathrm{max}{\displaystyle {\sum }_{{k}^{\prime }}{}_{i}{C}_{{i}^{\prime }{k}^{\prime }}}\)). Go to 8
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8.
Resolve \( j\)? (Yes => Go to 12; No => Go to 9)
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9.
\( i\)requests \( k\)from \( {i}^{\prime }\)such that \( {}_{i}{C}_{{i}^{\prime }k}=1\). Go to 10
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10.
Resolve task \( j\)? (Yes => Go to 12; No => Go to 11)
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11.
\( i\)acquired \( k\)? (Yes => Go to 9; No => Go to 7)
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12.
Task resolution
“Acquire on my own” type
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1.
Agent \( i\)tries to acquire the required knowledge \( k\) on his/her own. Go to 2
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2.
Resolve \( j\)? (Yes => Go to 3; No => Go to 1)
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3.
Task Resolution
Broad retrieval type
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1.
Agent \( i\)requests \( {i}^{\prime }\)’s TM \( {}_{{i}^{\prime }}{C}_{11},\cdots {,}_{{i}^{\prime }}{C}_{ASKS}\)from agent \( {i}^{\prime }\) (\( {i}^{\prime }=\mathrm{arg}\mathrm{max}{\displaystyle {\sum }_{{k}^{\prime }}{}_{i}{C}_{{i}^{\prime }{k}^{\prime }}}\)). Go to 2
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2.
Execute minimum effort type
Random type
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1.
(At the probability of \( {R}_{s}\)=> Go to 2; \( 1-{R}_{s}\)=> Go to 3)
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2.
Agent \( i\)tries to acquire the required knowledge \( k\)on his/her own. Go to 4
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3.
\( i\)requests \( k\)from agent \( {i}^{\prime }\), selected randomly. Go to 4
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4.
Resolve \( j\)? (Yes => Task resolution; No => Go to 1)
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Sakuma, S., Goto, Y., Takahashi, S. (2010). Analysis of Knowledge Retrieval Heuristics in Concurrent Software Development Teams. In: Takadama, K., Cioffi-Revilla, C., Deffuant, G. (eds) Simulating Interacting Agents and Social Phenomena. Agent-Based Social Systems, vol 7. Springer, Tokyo. https://doi.org/10.1007/978-4-431-99781-8_11
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DOI: https://doi.org/10.1007/978-4-431-99781-8_11
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